{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 基于 PyTorch  在 SecretFlow 中实现水平联邦音频分类任务\n",
    "\n",
    "## 引言\n",
    "本教程基于 PyTorch 的 [微软教程：使用 PyTorch 进行音频分类简介教程](https://learn.microsoft.com/zh-cn/training/modules/intro-audio-classification-pytorch/) 而改写，通过本教程，您将了解到现有的基于 PyTorch 的示例如何快速地迁移到 SecretFlow 隐语的联邦学习框架之下，实现模型的联邦学习化。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 单机模式\n",
    "\n",
    "### 小节引言\n",
    "\n",
    "本小节的代码主要来自于 [使用 PyTorch 进行音频分类简介教程](https://learn.microsoft.com/zh-cn/training/modules/intro-audio-classification-pytorch/) ，主要讲解如何在 PyTorch 下利用简单的神经网络进行音频分类。 为了教程的简洁，本小节仅仅简要介绍了一下各部分的功能；对于实现的具体解析，请读者移步参考[原教程](https://learn.microsoft.com/zh-cn/training/modules/intro-audio-classification-pytorch/)。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 安装 TorchAudio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: torch in /opt/anaconda3/envs/limingbo_sf/lib/python3.8/site-packages (from -r https://raw.githubusercontent.com/MicrosoftDocs/pytorchfundamentals/main/audio-pytorch/install-packages.txt (line 1)) (2.0.0)\n",
      "Requirement already satisfied: torchaudio in /opt/anaconda3/envs/limingbo_sf/lib/python3.8/site-packages (from -r https://raw.githubusercontent.com/MicrosoftDocs/pytorchfundamentals/main/audio-pytorch/install-packages.txt (line 2)) (2.0.1)\n",
      "Requirement already satisfied: soundfile in /opt/anaconda3/envs/limingbo_sf/lib/python3.8/site-packages (from -r https://raw.githubusercontent.com/MicrosoftDocs/pytorchfundamentals/main/audio-pytorch/install-packages.txt (line 3)) (0.12.1)\n",
      "Requirement already satisfied: sox in /opt/anaconda3/envs/limingbo_sf/lib/python3.8/site-packages (from -r https://raw.githubusercontent.com/MicrosoftDocs/pytorchfundamentals/main/audio-pytorch/install-packages.txt (line 4)) (1.4.1)\n",
      "Requirement already satisfied: filelock in /opt/anaconda3/envs/limingbo_sf/lib/python3.8/site-packages (from torch->-r https://raw.githubusercontent.com/MicrosoftDocs/pytorchfundamentals/main/audio-pytorch/install-packages.txt (line 1)) (3.12.4)\n",
      "Requirement already satisfied: typing-extensions in /opt/anaconda3/envs/limingbo_sf/lib/python3.8/site-packages (from torch->-r https://raw.githubusercontent.com/MicrosoftDocs/pytorchfundamentals/main/audio-pytorch/install-packages.txt (line 1)) (4.8.0)\n",
      "Requirement already satisfied: sympy in /opt/anaconda3/envs/limingbo_sf/lib/python3.8/site-packages (from torch->-r https://raw.githubusercontent.com/MicrosoftDocs/pytorchfundamentals/main/audio-pytorch/install-packages.txt (line 1)) (1.12)\n",
      "Requirement already satisfied: networkx in /opt/anaconda3/envs/limingbo_sf/lib/python3.8/site-packages (from torch->-r https://raw.githubusercontent.com/MicrosoftDocs/pytorchfundamentals/main/audio-pytorch/install-packages.txt (line 1)) (2.8.8)\n",
      "Requirement already satisfied: jinja2 in /opt/anaconda3/envs/limingbo_sf/lib/python3.8/site-packages (from torch->-r https://raw.githubusercontent.com/MicrosoftDocs/pytorchfundamentals/main/audio-pytorch/install-packages.txt (line 1)) (3.1.2)\n",
      "Requirement already satisfied: nvidia-cuda-nvrtc-cu11==11.7.99 in /opt/anaconda3/envs/limingbo_sf/lib/python3.8/site-packages (from torch->-r https://raw.githubusercontent.com/MicrosoftDocs/pytorchfundamentals/main/audio-pytorch/install-packages.txt (line 1)) (11.7.99)\n",
      "Requirement already satisfied: nvidia-cuda-runtime-cu11==11.7.99 in /opt/anaconda3/envs/limingbo_sf/lib/python3.8/site-packages (from torch->-r https://raw.githubusercontent.com/MicrosoftDocs/pytorchfundamentals/main/audio-pytorch/install-packages.txt (line 1)) (11.7.99)\n",
      "Requirement already satisfied: nvidia-cuda-cupti-cu11==11.7.101 in /opt/anaconda3/envs/limingbo_sf/lib/python3.8/site-packages (from torch->-r https://raw.githubusercontent.com/MicrosoftDocs/pytorchfundamentals/main/audio-pytorch/install-packages.txt (line 1)) (11.7.101)\n",
      "Requirement already satisfied: nvidia-cudnn-cu11==8.5.0.96 in /opt/anaconda3/envs/limingbo_sf/lib/python3.8/site-packages (from torch->-r https://raw.githubusercontent.com/MicrosoftDocs/pytorchfundamentals/main/audio-pytorch/install-packages.txt (line 1)) (8.5.0.96)\n",
      "Requirement already satisfied: nvidia-cublas-cu11==11.10.3.66 in /opt/anaconda3/envs/limingbo_sf/lib/python3.8/site-packages (from torch->-r https://raw.githubusercontent.com/MicrosoftDocs/pytorchfundamentals/main/audio-pytorch/install-packages.txt (line 1)) (11.10.3.66)\n",
      "Requirement already satisfied: nvidia-cufft-cu11==10.9.0.58 in /opt/anaconda3/envs/limingbo_sf/lib/python3.8/site-packages (from torch->-r https://raw.githubusercontent.com/MicrosoftDocs/pytorchfundamentals/main/audio-pytorch/install-packages.txt (line 1)) (10.9.0.58)\n",
      "Requirement already satisfied: nvidia-curand-cu11==10.2.10.91 in /opt/anaconda3/envs/limingbo_sf/lib/python3.8/site-packages (from torch->-r https://raw.githubusercontent.com/MicrosoftDocs/pytorchfundamentals/main/audio-pytorch/install-packages.txt (line 1)) (10.2.10.91)\n",
      "Requirement already satisfied: nvidia-cusolver-cu11==11.4.0.1 in /opt/anaconda3/envs/limingbo_sf/lib/python3.8/site-packages (from torch->-r https://raw.githubusercontent.com/MicrosoftDocs/pytorchfundamentals/main/audio-pytorch/install-packages.txt (line 1)) (11.4.0.1)\n",
      "Requirement already satisfied: nvidia-cusparse-cu11==11.7.4.91 in /opt/anaconda3/envs/limingbo_sf/lib/python3.8/site-packages (from torch->-r https://raw.githubusercontent.com/MicrosoftDocs/pytorchfundamentals/main/audio-pytorch/install-packages.txt (line 1)) (11.7.4.91)\n",
      "Requirement already satisfied: nvidia-nccl-cu11==2.14.3 in /opt/anaconda3/envs/limingbo_sf/lib/python3.8/site-packages (from torch->-r https://raw.githubusercontent.com/MicrosoftDocs/pytorchfundamentals/main/audio-pytorch/install-packages.txt (line 1)) (2.14.3)\n",
      "Requirement already satisfied: nvidia-nvtx-cu11==11.7.91 in /opt/anaconda3/envs/limingbo_sf/lib/python3.8/site-packages (from torch->-r https://raw.githubusercontent.com/MicrosoftDocs/pytorchfundamentals/main/audio-pytorch/install-packages.txt (line 1)) (11.7.91)\n",
      "Requirement already satisfied: triton==2.0.0 in /opt/anaconda3/envs/limingbo_sf/lib/python3.8/site-packages (from torch->-r https://raw.githubusercontent.com/MicrosoftDocs/pytorchfundamentals/main/audio-pytorch/install-packages.txt (line 1)) (2.0.0)\n",
      "Requirement already satisfied: setuptools in /opt/anaconda3/envs/limingbo_sf/lib/python3.8/site-packages (from nvidia-cublas-cu11==11.10.3.66->torch->-r https://raw.githubusercontent.com/MicrosoftDocs/pytorchfundamentals/main/audio-pytorch/install-packages.txt (line 1)) (68.0.0)\n",
      "Requirement already satisfied: wheel in /opt/anaconda3/envs/limingbo_sf/lib/python3.8/site-packages (from nvidia-cublas-cu11==11.10.3.66->torch->-r https://raw.githubusercontent.com/MicrosoftDocs/pytorchfundamentals/main/audio-pytorch/install-packages.txt (line 1)) (0.41.2)\n",
      "Requirement already satisfied: cmake in /opt/anaconda3/envs/limingbo_sf/lib/python3.8/site-packages (from triton==2.0.0->torch->-r https://raw.githubusercontent.com/MicrosoftDocs/pytorchfundamentals/main/audio-pytorch/install-packages.txt (line 1)) (3.27.6)\n",
      "Requirement already satisfied: lit in /opt/anaconda3/envs/limingbo_sf/lib/python3.8/site-packages (from triton==2.0.0->torch->-r https://raw.githubusercontent.com/MicrosoftDocs/pytorchfundamentals/main/audio-pytorch/install-packages.txt (line 1)) (17.0.2)\n",
      "Requirement already satisfied: cffi>=1.0 in /opt/anaconda3/envs/limingbo_sf/lib/python3.8/site-packages (from soundfile->-r https://raw.githubusercontent.com/MicrosoftDocs/pytorchfundamentals/main/audio-pytorch/install-packages.txt (line 3)) (1.16.0)\n",
      "Requirement already satisfied: numpy>=1.9.0 in /opt/anaconda3/envs/limingbo_sf/lib/python3.8/site-packages (from sox->-r https://raw.githubusercontent.com/MicrosoftDocs/pytorchfundamentals/main/audio-pytorch/install-packages.txt (line 4)) (1.23.5)\n",
      "Requirement already satisfied: pycparser in /opt/anaconda3/envs/limingbo_sf/lib/python3.8/site-packages (from cffi>=1.0->soundfile->-r https://raw.githubusercontent.com/MicrosoftDocs/pytorchfundamentals/main/audio-pytorch/install-packages.txt (line 3)) (2.21)\n",
      "Requirement already satisfied: MarkupSafe>=2.0 in /opt/anaconda3/envs/limingbo_sf/lib/python3.8/site-packages (from jinja2->torch->-r https://raw.githubusercontent.com/MicrosoftDocs/pytorchfundamentals/main/audio-pytorch/install-packages.txt (line 1)) (2.1.3)\n",
      "Requirement already satisfied: mpmath>=0.19 in /opt/anaconda3/envs/limingbo_sf/lib/python3.8/site-packages (from sympy->torch->-r https://raw.githubusercontent.com/MicrosoftDocs/pytorchfundamentals/main/audio-pytorch/install-packages.txt (line 1)) (1.3.0)\n"
     ]
    }
   ],
   "source": [
    "!pip install -r https://raw.githubusercontent.com/MicrosoftDocs/pytorchfundamentals/main/audio-pytorch/install-packages.txt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import the packages\n",
    "import os\n",
    "import torchaudio\n",
    "import IPython.display as ipd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 下载 speech commands 数据集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data directory will be: /home/limingbo/workshop/secretflow/docs/tutorial/data\n",
      "Data folder exists.\n"
     ]
    }
   ],
   "source": [
    "default_dir = os.getcwd()\n",
    "folder = 'data'\n",
    "print(f'Data directory will be: {default_dir}/{folder}')\n",
    "\n",
    "if os.path.isdir(folder):\n",
    "    print(\"Data folder exists.\")\n",
    "else:\n",
    "    print(\"Creating folder.\")\n",
    "    os.mkdir(folder)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "trainset_speechcommands = torchaudio.datasets.SPEECHCOMMANDS(\n",
    "    f'./{folder}/', download=True\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total Labels: 36 \n",
      "\n",
      "Label Names: ['follow', 'wow', 'learn', 'left', 'yes', 'stop', 'three', 'one', 'tree', 'seven', 'bed', 'on', 'off', 'up', 'right', 'down', 'dog', 'six', 'two', 'cat', 'sheila', 'eight', 'happy', 'four', 'visual', '_background_noise_', 'marvin', 'nine', 'bird', 'five', 'no', 'zero', 'backward', 'house', 'forward', 'go']\n"
     ]
    }
   ],
   "source": [
    "os.chdir(f'./{folder}/SpeechCommands/speech_commands_v0.02/')\n",
    "labels = [name for name in os.listdir('.') if os.path.isdir(name)]\n",
    "# back to default directory\n",
    "os.chdir(default_dir)\n",
    "print(f'Total Labels: {len(labels)} \\n')\n",
    "print(f'Label Names: {labels}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 把声音转换为张量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "waveform tensor with 3 frames:  tensor([[0.0005, 0.0007, 0.0005]]) \n",
      "\n",
      "waveform tensor with 2 frame_offsets: tensor([[0.0005, 0.0004, 0.0007]]) \n",
      "\n",
      "waveform tensor:  tensor([[0.0005, 0.0007, 0.0005,  ..., 0.0008, 0.0008, 0.0007]])\n"
     ]
    }
   ],
   "source": [
    "filename = \"./data/SpeechCommands/speech_commands_v0.02/yes/00f0204f_nohash_0.wav\"\n",
    "waveform, sample_rate = torchaudio.load(uri=filename, num_frames=3)\n",
    "print(f'waveform tensor with 3 frames:  {waveform} \\n')\n",
    "waveform, sample_rate = torchaudio.load(uri=filename, num_frames=3, frame_offset=2)\n",
    "print(f'waveform tensor with 2 frame_offsets: {waveform} \\n')\n",
    "waveform, sample_rate = torchaudio.load(uri=filename)\n",
    "print(f'waveform tensor:  {waveform}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 可视化波形"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_audio(filename):\n",
    "    waveform, sample_rate = torchaudio.load(filename)\n",
    "\n",
    "    print(\"Shape of waveform: {}\".format(waveform.size()))\n",
    "    print(\"Sample rate of waveform: {}\".format(sample_rate))\n",
    "\n",
    "    plt.figure()\n",
    "    plt.plot(waveform.t().numpy())\n",
    "\n",
    "    return waveform, sample_rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape of waveform: torch.Size([1, 16000])\n",
      "Sample rate of waveform: 16000\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio  controls=\"controls\" >\n",
       "                    <source 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\" type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "filename = \"./data/SpeechCommands/speech_commands_v0.02/yes/00f0204f_nohash_0.wav\"\n",
    "waveform, sample_rate = plot_audio(filename)\n",
    "ipd.Audio(waveform.numpy(), rate=sample_rate)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape of waveform: torch.Size([1, 16000])\n",
      "Sample rate of waveform: 16000\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio  controls=\"controls\" >\n",
       "                    <source 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\" type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "filename = \"./data/SpeechCommands/speech_commands_v0.02/no/0b40aa8e_nohash_0.wav\"\n",
    "waveform, sample_rate = plot_audio(filename)\n",
    "ipd.Audio(waveform.numpy(), rate=sample_rate)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 加载数据集文件夹进入 DataLoader"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import torch\n",
    "import torchaudio\n",
    "import matplotlib.pyplot as plt\n",
    "from torch.utils.data import Dataset, DataLoader\n",
    "from pathlib import Path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_audio_files(path: str, label: str):\n",
    "    dataset = []\n",
    "    walker = sorted(str(p) for p in Path(path).glob(f'*.wav'))\n",
    "\n",
    "    for i, file_path in enumerate(walker):\n",
    "        path, filename = os.path.split(file_path)\n",
    "        speaker, _ = os.path.splitext(filename)\n",
    "        speaker_id, utterance_number = speaker.split(\"_nohash_\")\n",
    "        utterance_number = int(utterance_number)\n",
    "\n",
    "        # Load audio\n",
    "        waveform, sample_rate = torchaudio.load(file_path)\n",
    "        dataset.append([waveform, sample_rate, label, speaker_id, utterance_number])\n",
    "\n",
    "    return dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "trainset_speechcommands_yes = load_audio_files(\n",
    "    './data/SpeechCommands/speech_commands_v0.02/yes', 'yes'\n",
    ")\n",
    "trainset_speechcommands_no = load_audio_files(\n",
    "    './data/SpeechCommands/speech_commands_v0.02/no', 'no'\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Length of yes dataset: 4044\n",
      "Length of no dataset: 3941\n"
     ]
    }
   ],
   "source": [
    "print(f'Length of yes dataset: {len(trainset_speechcommands_yes)}')\n",
    "print(f'Length of no dataset: {len(trainset_speechcommands_no)}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "trainloader_yes = torch.utils.data.DataLoader(\n",
    "    trainset_speechcommands_yes, batch_size=1, shuffle=True, num_workers=0\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "trainloader_no = torch.utils.data.DataLoader(\n",
    "    trainset_speechcommands_no, batch_size=1, shuffle=True, num_workers=0\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Yes Waveform: tensor([[-0.0028, -0.0054, -0.0034,  ..., -0.0011, -0.0013, -0.0014]])\n",
      "Yes Sample Rate: 16000\n",
      "Yes Label: yes\n",
      "Yes ID: 004ae714 \n",
      "\n",
      "No Waveform: tensor([[0.0072, 0.0061, 0.0055,  ..., 0.0098, 0.0085, 0.0092]])\n",
      "No Sample Rate: 16000\n",
      "No Label: no\n",
      "No ID: 012c8314\n"
     ]
    }
   ],
   "source": [
    "yes_waveform = trainset_speechcommands_yes[0][0]\n",
    "yes_sample_rate = trainset_speechcommands_yes[0][1]\n",
    "print(f'Yes Waveform: {yes_waveform}')\n",
    "print(f'Yes Sample Rate: {yes_sample_rate}')\n",
    "print(f'Yes Label: {trainset_speechcommands_yes[0][2]}')\n",
    "print(f'Yes ID: {trainset_speechcommands_yes[0][3]} \\n')\n",
    "\n",
    "no_waveform = trainset_speechcommands_no[0][0]\n",
    "no_sample_rate = trainset_speechcommands_no[0][1]\n",
    "print(f'No Waveform: {no_waveform}')\n",
    "print(f'No Sample Rate: {no_sample_rate}')\n",
    "print(f'No Label: {trainset_speechcommands_no[0][2]}')\n",
    "print(f'No ID: {trainset_speechcommands_no[0][3]}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 变换和可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "def show_waveform(waveform, sample_rate, label):\n",
    "    print(\n",
    "        \"Waveform: {}\\nSample rate: {}\\nLabels: {} \\n\".format(\n",
    "            waveform, sample_rate, label\n",
    "        )\n",
    "    )\n",
    "    new_sample_rate = sample_rate / 10\n",
    "\n",
    "    # Resample applies to a single channel, we resample first channel here\n",
    "    channel = 0\n",
    "    waveform_transformed = torchaudio.transforms.Resample(sample_rate, new_sample_rate)(\n",
    "        waveform[channel, :].view(1, -1)\n",
    "    )\n",
    "\n",
    "    print(\n",
    "        \"Shape of transformed waveform: {}\\nSample rate: {}\".format(\n",
    "            waveform_transformed.size(), new_sample_rate\n",
    "        )\n",
    "    )\n",
    "\n",
    "    plt.figure()\n",
    "    plt.plot(waveform_transformed[0, :].numpy())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Waveform: tensor([[-0.0028, -0.0054, -0.0034,  ..., -0.0011, -0.0013, -0.0014]])\n",
      "Sample rate: 16000\n",
      "Labels: yes \n",
      "\n",
      "Shape of transformed waveform: torch.Size([1, 1600])\n",
      "Sample rate: 1600.0\n"
     ]
    },
    {
     "data": {
      "image/png": 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bVVs22PKaf3VtW0HUFDHAISKrJGhl2NRR3oYzjm24aUSNxnVwiMgqKJUCDly4ARdHe7z6+1G0beZa72tLyisbGA4RkbVjgENEVuGnA5cwf8Nx8eu0rMJ6Xxs6dzP6t/M1RrWIyEJxiIqIrMLaw1fu6Pr9524YqCaWhzk4RNoY4BCRVeB7OBE1BAMcIiIisjkMcIjIKnAYhogaggEOEVkFxjdE1BAMcIjIKsjYhUNEDcAAh4isAsMbImoIBjhEZBXYgUNEDcEAh4isgox9OETUAAxwiIiIyOYwwCEi68AOHL34oyHSxgCHiKwC38T140aiRNq42SYRWbQrebcx9X+JOHGtwNxVISIrwh4cIrJob204zuCmDuzdItLGAIeILFpRWYW5q0BEVogBDhEREdkcBjhEZFFulVYg7mQWSisqAQACM2jrZcavKZj52xGUVlSivFJp7uoQmR2TjInIokxbmYxdp3PwZFRrvP1QmLmrYxWUArD28BUAwB/JlxHo4YT4OUO4fxc1aezBISKLsut0DgDg5wOXALAHpzEyC0pQoeQPjpo2BjhEZJH4/nxnGBhSU8cAh4gsmsBl7BqFPzdq6hjgEJHFil2VjKt5JeauhlVak3jZ3FUgMisGOERksTYevYb03GJzV8MqvbEu1dxVIDIrBjhERERkcxjgEBERkc1hgENEREQ2hwEOERER2RwGOERkFvm3y7HqYDpuFpWZuypEZIMY4BCRWfx3zRG89ucxPPNTormrQkQ2iAEOEZnF1hNZAIBDF29KjnP7JCIyBAY4RGRR7OWMcIjoznE3cSKyCLfLKnHwwg1UchMqIjIAk/TgLF26FCEhIXByckLfvn2RkJBQa/k1a9YgNDQUTk5O6NatGzZt2iQ5LwgC5s2bh+bNm8PZ2RnR0dE4c+aMMZtAREY2c00KJn1/iJtsEpFBGD3A+fXXXzFjxgzMnz8fycnJCA8PR0xMDLKzs3WW379/P8aNG4cpU6bg8OHDGDVqFEaNGoXU1Jplxz/44AMsXrwYy5Ytw8GDB+Hq6oqYmBiUlHDPGqqbwG2WLdKmY5nmroLNScsshCAIiDuZhSt5t81dHSKTkglGvtv37dsXvXv3xhdffAEAUCqVCA4OxgsvvIDZs2drlR87diyKioqwceNG8Vi/fv3Qo0cPLFu2DIIgICgoCDNnzsR///tfAEB+fj4CAgLwww8/4PHHH6+zTgUFBfD09ER+fj48PDwM1FKyBj8duIS561Lx5fheGNGtubmr06S1mfM3VHefi4tGImT23+atkA3q3NwDL0d3wDM/JQGo+jkTWbOGvH8btQenrKwMSUlJiI6OrvmGcjmio6MRHx+v85r4+HhJeQCIiYkRy1+4cAGZmZmSMp6enujbt6/e1ywtLUVBQYHkg5qeotIKzK3egPD5lclmro1tS7p0E2mZhbWWsVObLhV3MsvYVWqSissqsP/cDXNXg8gsjBrgXL9+HZWVlQgICJAcDwgIQGam7u7ozMzMWsur/m3Iay5cuBCenp7iR3BwcKPa01QplQIuXi+y+qGdjJvcldoUcgpLMfqr/Yj5bLfO35mS8kpsPZGFCrVkmyn/41o4xsCEbWrKmsQ08Tlz5iA/P1/8yMjIMHeVrMonW0/jno924ucDl8xdlTtyVSMHISO3KuApKa/Er4fSkVXAHC5DUP85llYoJeeKyyqw6J9TmPojAxpTUCoFq38wIWosowY4fn5+sLOzQ1aWtPs5KysLgYGBOq8JDAystbzq34a8pkKhgIeHh+SD6mfX6Rx8seMsAOC9TafMXJvGKymvRPoNaQ/OsSv5AIDP487g1T+O4bGvdQ9xUsPI1Yae1qdcQX5xOQDg3+OZ6DJvC37Yf9FMNWt6KpQCGN5QU2XUAMfR0RERERGIi4sTjymVSsTFxSEqKkrnNVFRUZLyALB161axfJs2bRAYGCgpU1BQgIMHD+p9TWocpVLAxO9qpvS39HY2Y20a71zOLXR7cwve/OuE5Pj5nFsAgM2pVUObl24UY9Oxa0jJyDN1FW1KaUWl+PmrfxzD2OVVgeMrfxw1V5WaLKUggB041FQZfaG/GTNmYOLEiYiMjESfPn3w2WefoaioCJMnTwYAPPnkk2jRogUWLlwIAJg+fToGDRqEjz/+GCNHjsTq1auRmJiI5cuXAwBkMhleeuklvPvuu+jQoQPatGmDuXPnIigoCKNGjTJ2c5qUvWevS772dHYwU00aJiO3GE4Odpiz9ijaNXNDeaWA8sqau7yvqyNuFJUhLeuW1rWq5OM3H+iCJ6NCIOequg1WUi4dljpVnWxsxz0YTK5SKYB9OGRqiRdzIZfL0KuVt1nrYfQAZ+zYscjJycG8efOQmZmJHj16YPPmzWKScHp6OuTymo6k/v37Y9WqVXjjjTfw2muvoUOHDli3bh3CwsLEMq+88gqKiorwzDPPIC8vDwMHDsTmzZvh5ORk7ObYpC93nkXB7QrMvi9Ucnz1oXTJ14mXbkIQBMgs+I0q/twN/OfbA+JT67aT2ust3d2xGf48fAUXrxfpfZ03/zqBFt4uuLdLgN4ypFuJWg+OOkv+vbFVFUwyJhMrLCnHo8uqem1Pvj0czo52ZquLSbZqiI2NRWxsrM5zO3fu1Do2ZswYjBkzRu/ryWQyvP3223j77bcNVcUmq6JSiQ82pwEAHotsibbN3AAAr/95TFx4rWcrLxxOzwMAHM7IM3tUrk9xWQU2p16rs0s+qp0v/jx8BenVScYX9AQ6p64VMMBphJIy3QEO95gyvUolh6jItC6p5Tqezb6Fbi09zVaXJjGLivQrLKkQP/9613mUlFdCEASsPFjTezNrWCfx83gLXVOjolKJLvO24H/xdc/0iulSlYyef7tc3NFal0zOqmoUfT04dgxwTK6SScZkYhdv1Dwwnr+unQZgSgxwmihBELA47gwGfbhDPPZrYgYW/H0ShaU1QY+3iwOi2vmivX9Vz87Ja5a5SOIvh+o39X9WTCd4ujjAz00BAPhoS5resrlFZQapmyUrLqvAxO8S8JMBlwAo1cjBUZHzbmNyTDImU1Pvwbl807zbg/CW00TFnczGJ1tPo0CtBweo2sog9XK++LWTgx1kMhmeHdQOALTKm8vm1GtY+M9J3C6rRHmlEv8er3sfoy/H98Lz91S1IzTQHQCQlqV/td2bxbYf4Px6KAO7TueIKzzfqbXJl/FPqu7/CyYZm14F18GxCmezb2Hg+9uteq2x1Cv5iF2VjF2nc8Rj5t7/zCQ5OGR5PvpXf8/F7jPXtY65KaoSxYpKK3C7rNKsiWMAMHf9ceQUlkKpFLAjLQdns2vvCv3fU30wqGMz8evBof6SWWLuCnsceysGALDnTA4mrEhAXvX6LQ1h6UnYmor15Ms0xs2iMsz47YjOc4IgcEaaGQgCUFahu0eNLMPNojJEf7ILAPDGulQ80a+1mWvUOOOWH5D0/rs62qFvGx8z1og9OE3WqVr2CUrPrRlDfSm6AwDAVVEVCydduonO8zYjZPbfqKg0z42zolKJnMJSAMA/qZl6g5spA9uIn7fwks6wc9EI0N59uGaWnq9r1fDVlbzbDWrj8yuTEP3JLpSUGy5oMDYnh5qfQ/kd/n/Wdn1G7m0Ul1rPz8WWrD18xdxVoFr8mqh/eH3f2et45fcjKCxp+MOWqakHNwDwyzP98FCPFmaqTRUGODYu/7b2H4bmir6tfFwkX5/PqQpwXh0eisciq/btUgU46g5eyDVUNRvk+q2aoSPNHojOzT0QGuiOPa8MxoD2vuLxIC/pIoVDO/tLvg5v6SV+3jHADR5O9igsqdA5hHU17zYOXaxp+/Gr+VifcgWbjmXiXE4RUq/ka11jqdRzqq7fKr2j16qsZSjk7g93MGmbmrz82+WShTABoFgjMEhUu7eM//Ygfku8jG5v/qtzX7HySiU+33YGB85b3uSPLs3Nv2MAAxwb9lP8RYS/9S+e+PYglGp/HJN/SJCUmxXTCXteGSx+rerd6R3iLQ63uOsIcG6VmicfR32vozyNPJlXh3fC5pfuRrCPCwa2b4anB7bB95N6w8VRWn9/dyc83LPm6SLEz1X83N5Ojta+VV9fy9N+U370q/0YsyxevBGNXLwX01eniOcbs/ZIpVLQ2ivL2PJvl+P3pMvi18mX8u7o9Soqmeth6VS9iyXllRi1dB8+3GK9269Yk9KKSuQVl6Hn2/9i2Ke7Jec0H9IeXRYPQRC0HkTbvbZJ3D9PZd76VHy67TQeX35A65yxnbxWgOKyCvG9xcFOOgRtb2f+8ML8NSCjmbv+OICqFYlX7L0gHj+XUzMEtSF2AO7v3hzBPi7wdXWUXO/lUvN1cy/tbRr+76ckcajIlNQDHM1Yoq2fm/i5o70cb9zfBYNDpb01Ku+MCsOEfq2xftoArXOBnlVDWtfya4KO9SlXMGvNEVzNr/r+fyRf1vlUpavXrC7zN6Si/6LteOLbgw2+trE0NxdNv8MbJHeutnyfbD0NANiQchUpGXlYuuOcmWtk+26XVeKeD3eix9tboRSqZhm9t+mkeP6ajp7NK3m38c2e81rHP912WvxcEARxrTIAGPLxTsNWvBbbTmThvs/3oMu8LYj5bDfKKpTo17amxzx2cHuT1aU2DHBsREZuMQpqGaddsOkkFsedwU21qc+P9GqB7i29xF4aza0YvFxqvnZT2OOV4Z2gqfeCbSafpfFvLWvXBPvUf78sN4U93hkVhvBgL61zfm5Vwd1NtUTjWb8fxRq1Ho+84nKtHiQAePGXw/Wug8rPB6rWHdp79jou3zTNk9iKPRckX+sKcDLzS3C7nonIXDXX8i3ffR4fbD5V672CDOtczi1cy5cGMct3n8eOtGwcu5wv9gRHtK5ZQPXSjWKd60bdUBuev3zztuRhqrxSMFn+35LtZ8TPz2TfQtKlm+LXUwa2wQtDGeDYnL+OXMWQj3di3nrDTLmtr5PXCjD041146vtDkuMBHgrJ159sPY2e72wVv1ZPwgUAD40Ax9tF2qPTNUj3ipTqPUKmoN6roi7E18VgM5jcqofkrubdhiAIOHG1QGs2Sk5hqSQfSKW0QqmzN+PC9SI8+tV+bDp2TXJ8+ylpwJZ48SZMQTO58ZeEdMn2FRm5xei3MA6d522uV0+dktORrcKXO8/hq501PTerE9JrKU13SnPLG5XJ3x/CA1/sRVZB1d/Wmw90Fdcb23oiCz/sv6h1zcUbReIDZbyOvJtzOaZZWK9U416Yf7tcnGTQI9gLCnvzzrJVYYBjQLdKK3A+p0grWldZefAS/lDrATCUtcmXUVapROKlm+K6A0mXcsU/HH1Uf0wqrX1rko1/+78orSeIge39dL6OelKcKeib9vr7c/0N9j3cFFXB3upDGXh0WTzm/HlMq8zRK/m4qifYuqVjvaBxyw8g8dJNPL8yWZLQu2T7WUm5ZbvOSXKmgNrzncorldh/7nq9e1pq86fajJsNR66Kn8/fUHfQzhwc63FDrSd39lrt320ynPUpV+suBKCFtzMe6B4EADqDG6CqZ2d9ylV8tfMcXvn9KACgbbOa/MEbOh64DE0QBHEiispfR66KGxo7WEDujYrl1MQGqAICXU/vN26V4vU/UzFzzRGDdyMWqb2xqZ7A43RsMqnuiX6ttKLsHmpDNZrBD1DVvqcGtIG9XIa/YgeKx2evPWbStTbK9LyRqlYnNgQ3p5qk5KRLN3EkI0+7HhVKpKRrHweAwlLtIQD1WUTJ1V26x6/mi/t8qZzKLMT2UzX/f19sP4Ow+VvQ8fV/dK44vGLvBfznm4N4+Mt99R4u/GZ3zfj+u6PCxOUAVIFXWYUSH6qt8qxZR12Yg0OkraW3S92FULVqfJCX9obR66YNwCePhYtfL9l+Bu9vrkkOv7tDM/SpXm+mMfl/upSUVyKnsBSCIKCotALHr+aL95abxeUo01gS4u9j18RhKoW95YQVllMTG6DaTFBXLsJn22rGLDVXyP0p/iKe+zkJB8/fkMxqqY9KpYBVavtGqfIoTldPb35hSHvMuLej1nUyaA/lqK+J4qUxXKUy9/7OSJk/TGsDNVMmx5ZXB1NL/9MLsYPbo4WXM1Y+3deg30PXrDFdPo+r+n+NaO2Nc++NEIOsQo0eHM2poYUlFUjLLMTIxXt1vu6hSzW9Yh/9W5VYWFap1Lni8HfVCeSnMgt15icJgoC1yZfxV3WPTHFZBRaoJTkO6thM/P9WLW6YoZEHVJ8ZcxVKLihHpJJTWIpzObfqtcnsWw92hUwm01qOY9Ej3dAj2EvSm66ZEuCqsBNzAWf8lnLnFQcQuyoZvRdsQ5s5m9B1/haMXLwXO6tXKM4urH25B0vqweFKxgZU04OjfaNXf/K+casMzT1rkmFVs51US9y38nERI/K67EyT9tTkFJaitKJSXC57aOcAdGvhKc6eUHnm7rZarxVVnQXv4mind9VZmUwm5qdEtPYWo/aEi7n4YvsZxA7pUK963wnVWK+3qwP+G9MJ/43RTn6+U12CGraGg7eLA+zkMrg72eP6rVJJgPPJv2lYrDEMNXPNEbw+orPW68yK6YQPt6Th613ncVf7ZkjJ0M7HKSqtEG+ESqWAbLX8mG92n0dM10BJ+fjzN8QVhgeH+iNbY9aGr5ujOGMu73bVjTJJIw+orqfQkvJKk+diEVmy3gu21busd/UMVs0V4h/p1RKAds6LOjeFAzJyq4bKyysFZOQWI9infr1G+mzTMQLw26EMDO7kX2fqg+Z0cXOynFDLBqgCnLpyEdQXyDujYyG50xrHbpdV4ujlPOw5k4NHvtwnCVY01z74ZOtpdHpjM8orBchkQLcWnrCTy/D2Q13FMoEeTjr/AEL8XLHlpbuxa9ZgrXO6fDW+l+Trtck1+Rt5xWUGyQnRRRXgOBrxSSGshSd+mdoP04fWBGzNPZ0wuvqGE+gh7UqeFRMKoGYmmvqQlmZwo6LqRfFzU2DdtAHY8tLdksDqiRUHxd4bderTu1drbDKaeOkmTlytWbzvy51n8Z9vanrXbhaVSfIvAMDF0V68warG8PdUb2OhSlQ/lVmg9XupbsyyePx3je5tGoiaisPpN9HvvTi8u/GE1rm593dBwutD8cdzUVpLcjSvXpbCxUEa4DhWD/fo61EHqobTf5rSR/xaNb28pLwSqxPSGzxsVVymu7dW9f6mekDqHeKts5wDh6hsk72eHBzNvIh3Np5ASkYeViek416NRZ+AqqRhdc/8lIgHv9iHCSsSkJyeh8VxZ8TXLK4ln8fbxVH8pVRfMnvxuJ56r+kU6I5m7vXLZfH3cMKh16PhU/3Hev56EbadyEJWQQnu/mAHRn+1H38kXdY5lfpOmCqZLaqdL16+tyMS34jGy9Ed8efzA/Dho91x8LWhmDQgRFJWNa1cFbCqDwHVZe79ndEj2AudAt3RU8eUdU0JagHyazqSn1UzKf45dg0fbJbuOZZ/uxzXdcyICvau6lE8n1OEw+k3xcB53v1dEdnaG4IAHKxltdRjVrR6M2nbd/a6wfI3DOHbPefx2bbTDV6CIqewFGO/jsf6FPNsT/HEtweRWVCCb/de0Do3JNQf/u5OiGjtg8Q3orH31cF4pGcL/HdYR0RWTxFXX5BUPXl4aOcAPBmle4+qmC4BiAzxwYLq7WZUE1nmrD2G2WuPYcHf2sFWbdQfkNQ52sshCAL+Olo1C7S1r6uYu6fO2cEyZlABDHAMyk5e9ePUXLJe19S9UUv36Z29kJyehyK1nIc9Oja/VOVKqFa/ddWx+aX63kCezg44/94InHtvRL2Hv+qjmbsC8XOGiF8//WMi1iZfQUFJBU5cK8DMNUcwZlm8wb4fADHBzdFETwp+bgpMj+6AQE8nyOUyBHg4YWJUiKSMakq9esK3rr2Z2qqtmKyivv6Fl8bUfF3Uf2905QqpnsCeW5msdS7/drlkh9+vJ0QAqBqCksuqfrYPf7kfKdU9UM29nNC7+vdF3y7hZP3Gf3sQo5buE7+uqFQi9Uq+3sTxikolcosa9+CiWnZB395l+cXlePfvk/hs2xmcuKb7zVaXwpJy9F6wDQcv5GL66hST75VXWFIu+ftX5+FkL/bSAFVD/S29XfDJ2B6IHdJBXN5C4VBzT1te/bcJoLoXPgzP3dNOPNa9pSfOvzcC/tW9yf7uVf8WlVXiVGaBOCPyt0TdeZ1z1h7D0I93ai27kaJjQgVQNTN0w5Gr2F2d/tC5uQeeHdQOXTWG893qmb9oCgxwDEhXD86OtGxEf6LdS1MXzbVSNGUVlmDPmRxxgbjuLb1wX1ggXhhSs8CSZqKrXC7TuXjUndKcjaWe4Q9ULQRlSKoZW+ZMZnN2tMOKiZEAgBZezmLO0veTeotlrubdxoXrReLvxfeTe2PLy3dLXmdsZLBWfsva5+ue7j71x0QcTr8pft/QQHfxnOr/XdeT1NnsW7hUvQT88/e0E/N1HO3lWvt1AVVd56rcLPU1csj2XLheJPbcvb3xBO5fshdLd+geXv1462lEvLtV0puoLunSTbSZ8zc++TdN69yKvRcwYvEevKbnAe9kZk1Qo/lwtzMtGz3e/hf/HtcOto9elvYimnKT0eu3SrHgb/29tklz75VM4tAn2NsFPq6OaNfMFe2aac9kfXZQTYDzxsguklxJ9dyXhZuk92Bda4f9kpCOczlFiFq4HT/sq+lxyqmeSdm9pSee6NcKHz7aHUDVLFD1LWl6BHvBycFOzBNS0dzI2JwY4BiQZg5OcvpNTNZYfE8fDydp1Dureo0DfU9Jl3NvY8KKmj2lugR54KsnIjBzmOETbg1Bc12XO2GKHJz6GBLqjx+f6oN1als9DA71R4vqQGHPmesY/tlucVZdgLsTHOzkuL97c7H8mw92haZeraRj2z8+1UerzNYTWXj4y/3isML8B2pe51ZpBUorKrWmcgJVOVqq6eqaAU0bHb1L/u5O4tRVXcOhxy7nY9CHO7SOk3X6tTqn68f4qkkRmpMTVL7aeQ6CAMz+46jO8y/+chiCUJV/dumGNDBWzShdo2fGqHqOmfqil4IgYNL3h5BXXI45OoIjzdk9pzP154wZkiAIGLBou1Y+nMq590bU+2HM2dEOu18ZjH+m361z0VL19wnNnhL1nnnVJBOVi9drXx39zb9OiMPdqkU9h4cF4t1R3cT7gmYAqcrPu6GxSa+ujZnNhQGOAWn24Ow/qz20pG9Y5Z1RYeiuMfUa0E44vqtD1WJ7yzX2KXn6LumqxKa2pJa8HgC4pSdxrTFUAY6DvXmz9WUyGe7u2EwrZ0k1BPTGulTJ7AfNGRIA4ORQ95/g3R2b4eKikTj33gi9Zbq39BRnxp3LKcLVvBJUKgW4ONrh7Ye6Ytrgqie//Nvl4s7DqrwhlT4h2kOXdnIZnKvzAopLtQOcF1cfFnuEyPrZ12MGjHpejL7ZPer5PIM+3Ck5p97DnaqRu1VaUSnpJTibXXP/e+3PmiUSVA+T6nX5I0naY/Pt3gtas0yN4UZRmd6fQwd/twb3mrsp7PW+T8hkMnz+eA/MiumkNdPTxdEerw4P1Xldeq40yNT1wLnqYDqyC0vENa9UPcsd/N21ygIQ73vqmxYDXAfHZql+kdOyCvVmoj8UHiT5OjTQHZ+N7YH7uwdhQ+xAjI0MBgB0CnDHkYw8yZLqQE22vWbXsI9aVv5nY3vAwU6mNcvJmB4ID8IX/9Ef5OQXGyaBsVIpiEnG9nLr+vXVFcw0ZGuJ2m6ULo524lh40sVcsefPx9URT0aF4L9qPXuqISxfjYUR22ks7qj6dqr8rrJKpVbehKn2vqHGGdYloEHlda3ZopmTMW1VTW6XvjyaToHSN0XVsPKaxAzcVvudmb/hOA6n1/TSxJ+TJrJfzSsRg5hf1LaUqFAKePp/h/DQ0n2oqFSipLxS5/5ak+rZg34nNPdw66D2d2To4XmgasLIND2bWYbreEgGgFf/OCZZi+u2nr/b5Et5uFA9FD2oQzMAgKeLA+be30UsExrojgUPh4mpCR0C3MVhLKBh9zRjs653CAun/vTzv/2XUFKu/cc/X2NIwk1hj1E9W4hvXo/0qoqGyyqVeGjpPklXY982Pgjw0F7pEpDmwYzq2QLH3xqO+7o111nWWO7vHoTtMwdh2uB2YjtUDDFDo6JSiQ+2VI0tuyvsJUGdJZl9n+6nKFVOjOampro09KlPJpOhb5uqXJmswlIxwFElP8tkMsn4PaA91V3zd+vflwdV1Vut56lYI4nSkp7WSNu4Pq0aVN6+eihF/ddv1NJ92Fa9gKTmDtY3isp0Psypb74I1KyvpBp6Vy/38Jf7xQegPI0HobJKJQpua79+blEZtp3MxtHL+ThyOR+hczeLQyi1tfnC9SKdS3PUJb+4HLGrkrHjlHaPkGpIJ8TXBe881BXvPdKtwa9vKFHtfPWe+6l62LFSKeDbPdqzvICaHjU3hT081TZbntQ/BAPa+6J/O19sfGEgxveVzuh6NKIlnh3UThLoWALenQzITq1H4f3Np/CFjgQ9zXHTu6qjZBXVL5XmuOajES3x3aTeYsZ8XUw1w0hT22ZumBUTik8e64ENsTW5KQUaAU5GbrFW97S6/Wev452NJyRbQKw9fAVf76oamuvTxscoCdOGcLfG/6mKKrAZ1FH3eXWqWVqDO0nLxup5cgOqhpzksqobmGpqqPqO8P4aQ2ktvaU5OGEtPMRh0hUTI8XtOhzt5OLPWnNtI0vZVI8Mw14uw//9lAjNEYynf0xEQUm5Vm9OpVLASbWZToIg4Mf4i1qvm19cXuu6WGerZ5pev6W9hMHaw7Wv7q6ZbzKsq7TXShXQrDqYjsEf7cS9n+6W5PnUx7wNqdh49Bom/1DVI6Q+zKYK8IJ9XDAhKkSySXFooO7hHWORyWT4blKk+PW2GTWTGlTpDmuTL+PTbbpzq1TvWZqdMHZyGVY+3Q+rpvYTg2DN7zv7vlCMqR6BsBQMcAyoriW511cno/4ytR/GRgbj3VFhePYe6YrCrtX5DgUaM6AejWgJV4U9WujYq0RX7oQl6N7SS5wCrdl9fNcHO3D/kr3I1LExaUWlEv/59iBW7L2Ajm/8I87eOaDWfR1ej/VizMXPXbtnafmECLHr9t4uAVj0SDdJcrKmV4Z3wrIneuFzjdym/8Z0wsVFI/HUgJqcq6X/qRqKtLeTiws4XqzOi1GfSTVabbbDwz1baHUlK+ztsCF2IC4uGomhnWveJGQymbgAmXrXtiAIkmmtZJ3eH13T41BWqcSW49rbfQBVq2RrJpoCEFfJBoCfD1zCvOqV2QEgqHpI/WaxdHkCTarF43RNqnjrr9rXcVkcd0bydWsfFxyYM1T8+t8TWRAEAfPW1+Tw9H0vDjsakJ+zV20214u/HEa71zaJW58UVeemqWYPqfdqLnsiAqY2JDQA594bgYuLRqK9vzvee7jq//e3xMtaD5b69u/TnIFrrXh3MqC6ehRUb8pR7Xzx/qPd8US/1lpPwPoy0FWZ7FFt/cRZOkvG9UT8nCH44aneOq+xBKpei2d/ThZvXup5GxuOXEFyurQ7W3Oa+T0f7URRaYVk2qf6TCRL00zjpvHB6O4YprZ9gkwmw+N9Wkk2N9Xk5GCH4WHN4eGkezhrzohQtPByhp+bIwZ2qNnlPayFdAxePbD0dHHAmQX34cvxvfDuqLCGNEnsEVT1qJWUVyLms9063/DIgtSjk3Ns75ohneuF+te2ySsu17kInCrJPL+4XNx2BqgaRlb1OOcVl+HyTf3J6Gezb2H/uetiPsv4vtrDTKohVW+X2od43RT2CFRbcyYlIw9fbD+rtUfgrrQczUv1Uk8i3lAd2Lzwy2EANT04qkX6vNWGzjV7SU1F/b1IfSj/uZVJko2EOwa4YbjG1i62hAGOAdWWW6U5DVwffWsIqIYXnB3tsOnFu3Bk3jA8EB6E5p7OktUvLY16vonqSStHbSXd9zadwuNfH5CsdvyNjvFh9d21QwPd0VbHGhGWQiaTYUD7mrHwlj6Gv8k52Mmx8YWB2PzS3ZKf8QPdpUnsmssGONjJMaJb8wZP5VQ9laoSFbedzMLpLMMnUJJh1RXf/Fm95tKEflU5Fd/tk/7t9VfL6cgpLMWviVVTof9vUFvJuitnsgoR/va/kmtnjwgVh0jzistx+ab+HpyPt57Gf745iI3Vq+SGNtfeC66k+ndPcxkFTe7VDwWvjajKhdt6Igsf65ju3pDexzI9s6QmfpeA96rXnFHdu90U9tj4wkD8+/LdOodzTE09yEq9UgBHO7VNlV0cMO+BLlrXfGBhuTSNZf6fvg2pbQ8qfZtXatKXtKk+nODp4iBJALNk7dVmFKgCmxyNcfaySmWtNz9AOp20vnlI5vTNkzXj4G39jBOMebs6anUx39OpmdjDt33mIPQ20PClZg/OTQPNiiPzObvgPvSsDhZ09T538HfDW2qTIhLVdrivrBSw5tmaBSk1t5zxc3PEyG7NxXyUvNtlOHo5Tzz/zqgwbHxhILroCGQAwMfFEbPUNtHdeiJLTEBW38JAXQsvZ/zxXH8xKV7XquD92/mKQ/qlOiaB6KPUs2WEev6P+kNDWAtPdAwwbf6NPl2DPCRLQqjn31QqBQR5OeNLjRm3j1lYLk1jMcAxIF0Lq6l8Nb5+Y7G6ptgNbO+no6R1UE+oVQV5uvZCevbnJABVf3C6esK+3l2z7o+5F/irDxfHqg3wlj3RS9JdbmxODnbYN3sILi4aadBeLtVQqqqrvrjUNsbom4JVU/sCqJqFqU69d0HXG/jWGYMkv0PqwzQDOvghvKWn3nWcDr4WDS8XR7EHJzO/VNwy4OXojpjQrzXCWnjijfs767ze29UBU++qyU+c+mMigKrAacrAtlozAAGgV2tvybYnQ0L9tcq09nUR1xJTnzatLqewFLPWHMHh9JsorajEwn9OisNbQ0P9EaynR1ZzA01LIZPJcOj1aPRs5aV1rmtQ1ZC2pdb9Tln+O4UV8XPVnbD1yWPhtU7fq82QUH98/niPO6iVeamvjltaXokjGXlIrR7HV78ZXb55G4IgoOB2OeraX0/fNGxLc1eHZhgeZrm5Qg2h6s5X9eDoW/+ELItMJkP/dn64uGgkfv2/KMTPGYIxES2x8YWBknLBGtuF9Kp+M7STy8Rp16rE0xHdAnFPx2aQyWQ6l8L44j89xR4hVZ6Z+oJ76n/3ugIVoGp5A0d7OVr5SOs1PCwQgZ5O2PXKPTgyf5jkXKnG2i5+bgqtdvYI9hJ/l3XVHQDmrkvFmqTLePjL/fh+30Vx5qajnRzfTozEnleG4MWh2ptM9m9nuQ+iMplMa2jP19VRXBy0m571c6wdAxwDauXrgi/+0xP3dgmAu5M9nB3sMLxroGQn74YI8nTCd5N6ay3IZk1cFfbiVOd/T2ThoaX7xFycDv5u4swyoGpNja3V623o2jwUqFqxt72/5ebf2CpVr5nqqVffQmFkPpP6h9RZprmnMz4cE66VjD6+nzSpN1ptgUDNv8XBnfxrXcxNPWm1Z3DVm+p5tX3M1B/29PVuqgIfzd+zJ6uXT1DY28HT2UGyHEbfttoPkWEtPCXDbz2CvcU9ofT14KivHr/on5oJD83cFWK7NVcvB3TPnrQkmg+Obz8UJv4sXBztMbV6NfwxES01L7ValpudaqXu7x6E+zUSPRtLc1dya/VgjyDs0DFjIcTPFeHBXvBwskdBSQUi390mnvNzV6CbpxNOZRZKFv/qacHTw22Z6qlXNUxxu4w9OJbmzQe74of9Fxt1reZEhY5qy/NrbhKpngPXJ8QHCRelq6qrD3219HaGg51MXH1cYS+XBBzq39fPTYEfn+qDW6UV4kykIE8nyaSEDhoPN3tfHYz4czeQV1yud4G/dx4Kw2t/HoOLox06BrghJaNq1qauHJyvdp6TBGPq1B+s2urYt81bR86PJRFQ837iprCX7F0FAK+P7IIno0J0brprrdiDY4FUT2LWMhRTF1c9s7xUWwvoWoshyNMZq57uhwNzhoqbugHAs/e00ypLxlfTg1Md4LAHxyo0dinMoZ1r8lc0hy/UZ3rWtUSFXC6Dp3PNG7+u/dhUHo1oiS5BHpI33k/H9hA///dl7Q0o/d2d8FCPFpjYP0Tv4qb/6dsKCa8NxfG3YiCTycSArUSjByc5/abWEhXq1LefCGvhCXeNmYj12S3cnNSfl+PnDNHZCxXs42KxC6g2BntwLNC8+7tgysA24qJt1s5Bz41HleDmrmMKvavCDnK5DE5yOxyYMxTz1h9HKx8XNPe0nacLayImGZdXIvFirmRfILJcDdkW6PtJvfFj/EUsGt1dEkho7melvniki6M9zi64D29vPIEf4y/pXPfFy8VBXKHYRUcQ8OnYcGxOzUTsEO1Vuts2c8PFRSPr3wg91HudVL/L6isrn8kqxCNf7q/1Ndqpzd7ydHZA3MxBUNjbYdHmk0abKWlI93dvjh/2X0SIr4s4ld7WMcCxQHK5zGaCGwC4S2MW2MM9W8DfQyEuQKXrj039aUMmk+GdBi5MR4bl7Vr1f6S+kBtZPn/3+s/gGxzqj8E6Zh7JZDK8+UAXvFm9orBmT4W9nRyvjeiMHsFektwd8Xq1zzUX2wOAh3u2xMM9TZf3oXqgulU9E7CwpByPLz9Q53UPaGyUrAqaFj5iHWvGRIb44J/pd5lt8UFzYIBDRmdvJ8exN4fh7b9O4P7wIK29mHT14HAoyrJcv6V/hVuyTO+P7qa1q3djdVfLfdM1zOTkYIdHeukOUvLU9qHL1rFEhKmp7jeqWWEfbknDjepV1nu28oKbwh571LZmaOauwO5Zg2sdXrMWnfWsO2SrGOCQSbg7OeDDMeE6z2muErpiYqTBFqgjw9CcrkuWT30LhjvlpLaljHMDc00c1HI6Xh+he90bU1L1GKs2AP6xepdtoGpblbbN3NDutU0AgK8nRKBfW1+bCG6aIgY4ZHbqs8UMMd5OhjdtcHus2Ctdxr9nKy8cTs8zT4XIpNQTTxsa4IQ298DV6k11n76rTR2ljU+1bU5RWSUSLkhngPm6KWAnl2H3rMG4lFuEuzo00/USZCU4i4rM7oUhVYtmjexmG4vi2SIfV0etKbq1bdJ3r45cDLJe6jNu9G0no8+Ch8MQ3dkfP0/pW+v6OaaivnfbrN+PSM55VZ9r5evC4MYGsAeHzC6itTf2vDJYsustWZ7iMum0Wn3rfsy4tyNiB7dH2+pufrJ+Pq6O+GlKHzg52NV7Xz2V5p7O+HZi7dPJTcneTo4FD4fh9T9TxZ3QAzwUWDGxd4PbRpaNAQ5ZBFuaNWarbqntP3XszWHYd/a6znJ2chnfKGyQLfVoqG8XAQBP9G2ttbozWT8OURFRvRSX1QQ47k4O4k7UmlT5GmMiWiKcK0+TBWrtI12JmAG5bWKAQ0T1olpuXyXAwwmrn+mnVc6uOs/iwzHh+KV6J2syjf891QcAcE8n2+ltMQZnRzvJDtq2tP8S1eAQFRHVi2rPMHX9dGxwqJ7EaUvLvluDQR2bYf/sIQjQs0s31YibOQhFZZVoYUN7L5EUe3CIqF6+n9wH4cFe+OO5qFrLqe+qbGcBs2aamiAvZwaW9eDl4sjgxsaxB4eI6iWitTfWTxtQZznNHpwgTydxHRQiIlNhDw4RGcxTA9qgl1rysUwmw65XBmPjCwPNWCsiaorYg0NEBqGwl2PeA120jjvYyeGm4K2GiEyLPThEZBAOdvpvJ/Z2zAkhItNigENEd0Q13VbXjCqV2oIfIiJjYL8xEd2RP57rjzVJGZgysK3eMg2Z1TN9aAeEBrrjuZXJhqgeETVRDHCI6I6E+LliVkxorWUaMl18fL9WzNlpoJ3/vcfcVSCyOOw3JiKjc3a0q3dZO5kMcq6fU28D2vsixM+17oJETQwDHCIyOicHO3zzZCQ+GN29zrJ2chnsuVBdvbk6sreLSBf+ZRCRSdzbJQBA1YyqC9eLsGT7WZ3l5HIZV+Ktp65BHpj/YFdzV4PIIrEHh4hM6pFeLfFAeJDe83YyGWQcoqqX9dMGcLsBIj0Y4BCRybX1c0XbZq5wtNe+BbH3pv4YCBLpxwCHiEzO3k6OrS8Pwu/Pam/cyQRjIjIEBjhEZBb6emrYg1N//EkR6ccAh4jMRhC0jzG+ISJDYIBDRGajI75hXkkD8EdFpB8DHCIyGycH3oKIyDh4dyEis+kU4I4no1ojSsdGnR+M7o6xkcFmqJX1YG8XkX4McIjIbGQyGd5+KAxzRmjvZfVY72C89RAXsSOixuFKxkRkdt1beuGFIe3R0lu6aB07KIiosRjgEJFFmDmsk9YxGSdCE1EjcYiKiCwWp4wTUWMxwCEii8UkWiJqLAY4RGSxGN4QUWMxwCEii8UOHCJqLAY4RGSxOERFRI1ltAAnNzcX48ePh4eHB7y8vDBlyhTcunWr1mtKSkowbdo0+Pr6ws3NDaNHj0ZWVpakzIsvvoiIiAgoFAr06NHDWNUnIiIiK2a0AGf8+PE4fvw4tm7dio0bN2L37t145plnar3m5Zdfxl9//YU1a9Zg165duHr1Kh555BGtck899RTGjh1rrKoTERGRlTPKOjgnT57E5s2bcejQIURGRgIAlixZghEjRuCjjz5CUFCQ1jX5+flYsWIFVq1ahSFDhgAAvv/+e3Tu3BkHDhxAv379AACLFy8GAOTk5ODo0aPGqD4RERFZOaP04MTHx8PLy0sMbgAgOjoacrkcBw8e1HlNUlISysvLER0dLR4LDQ1Fq1atEB8ff0f1KS0tRUFBgeSDiIiIbJdRApzMzEz4+/tLjtnb28PHxweZmZl6r3F0dISXl5fkeEBAgN5r6mvhwoXw9PQUP4KDuYEfERGRLWtQgDN79mzIZLJaP06dOmWsujbanDlzkJ+fL35kZGSYu0pERERkRA3KwZk5cyYmTZpUa5m2bdsiMDAQ2dnZkuMVFRXIzc1FYGCgzusCAwNRVlaGvLw8SS9OVlaW3mvqS6FQQKFQ3NFrEJHlG9DeF/vO3jB3NYjIAjQowGnWrBmaNWtWZ7moqCjk5eUhKSkJERERAIDt27dDqVSib9++Oq+JiIiAg4MD4uLiMHr0aABAWloa0tPTERUV1ZBqElETxc05iUjFKDk4nTt3xvDhwzF16lQkJCRg3759iI2NxeOPPy7OoLpy5QpCQ0ORkJAAAPD09MSUKVMwY8YM7NixA0lJSZg8eTKioqLEGVQAcPbsWaSkpCAzMxO3b99GSkoKUlJSUFZWZoymEJGFGdDeFwp73bcuAYKJa2Nc9txtlKjRjDJNHABWrlyJ2NhYDB06FHK5HKNHjxaneANAeXk50tLSUFxcLB779NNPxbKlpaWIiYnBl19+KXndp59+Grt27RK/7tmzJwDgwoULCAkJMVZziMhCPH9Pe/Rt44P2r/9j7qoQkQUzWoDj4+ODVatW6T0fEhICQZA+bTk5OWHp0qVYunSp3ut27txpqCoSkRWSAbC3axq7zKjvVPF/d7fF17vPm68yRFbGaAEOEZExyDlsg94h3mjv72buahBZNAY4RGQVmrkr0MbPFb1DfPSWEWwrBUevX6b2azK9WESNxQCHiKzC95N6I6yFp7mrYVJVs8KaSNRGZGB8BCAii/bjU32w4OGwegU3sgaOXh1/KwatfV0aWTPzkTW0oURNEHtwiMii3d2x7rW3VBo6ROWqsIejJQ/1MI4hajQL/ssmImqYYO+G98ZYY2eIFVaZyOTYg0NENmPOiFBUKAWE+Lrg462nzV2dRvFwskdBSYW5q0Fk9diDQ0Q2w8vFER8/Fo6odr7mrkqj3RfWXPcJdtsQNQgDHCJq0qxx/yprHFYjMjUGOEREFopxDFHjMcAhIrJQHzzaXedxThMnqhsDHCJq0iw5VnioRwtzV4HIajHAISIiIpvDAIeIiIhsDgMcIrI5HQLctY51b+kJDyd7uDtZ5/Jf1jjbi8icGOAQkVXaNuNuvD6iM0b3agkA6Ka2V5WnswMOvR6NY28OE4890D0IKfOGoV9b61wjR+Cmm0QNYp2PMkTU5LX3d0d7f3fcLqvEXR38MEhjz6pm7gqta+RyWYP3qyIi68QeHCKyas6OdhjVswW8XR3rVX7qXW0AADFdA4xZLYPjEBVRw7AHh4ialL5tfZH0RjS8XeoXEFkK33oGcERUhT04RNTk+LopIJdX9YhY+qJ5i8f1xAtD2mNUT66JQ9QQ7MEhIrJgD4YHiZ//8Vx/uCrszFgbIuvBHhwiIgvQubkHfpnar9YyEa29ERroYaIaEVk3BjhE1KRZygDVphcHIqqddU5hJ7JEDHCIiIjI5jDAISKyAJae7ExkbRjgEFGTEOjppPM44woi28RZVERk076bFImkSzcxsltzc1eFiEyIAQ4R2bQhoQEYEmpdqxYT0Z3jEBURNWkcoiKyTQxwiIiIyOYwwCEisiDsUSIyDAY4REREZHMY4BAREZHNYYBDRE2azGI2ayAiQ2KAQ0RERDaH6+AQEZnR7lmD4e7EWzGRobEHh4iatBA/V4O8zmORLRt1XUtvZ3i7OhqkDkRUg48NRNSkvflAFyjs5QjwUGDpjnONfp3n7mmP3xIv17v8xhcGwt9dAbmcOUBExsAeHCJq0nzdFPhoTDgiW/voPP/Hc1H1ep2GhilBXs7w99C9ASgR3TkGOEREgN4Ixd+dQQiRNWKAQ0TUQCsmRuKeTs3wxsjOjX4NQRB0Hm/l69Lo1ySiGszBISKqha6tE4Z2DsDQzgHYcOSqwb/fUwPa4HphGaI7+xv8tYmaEgY4RERmINOz6ZSTgx3mPdDFxLUhsj0coiIiqoW+QORO6RuiIiLDYIBDRNRInOBNZLkY4BARNZKROneIyACYg0NE1EjRnQPQ1s8VPVt5m7sqRKSBAQ4RUSM5OdghbuYgyGQyXLxeZO7qEJEaDlEREdWirlEoYyUhE9GdYYBDRASgS3MPk30vmQzwdHYw2fcjaoo4REVEBCDAwwkD2vti39kbRv0+W1++Gy29XWBvx+dLImPiXxgRUbXWvq5G/x5ODnZwdrQz+vchauoY4BAREZHNYYBDRERENocBDhEREdkcBjhERLXgLHAi68QAh4iIiGwOAxwiIiKyOQxwiIiIyOYwwCEiIiKbwwCHiKgWMsjw94sD0auVV+3lmIxMZFEY4BAR1aFrkCcGdfSvtYwgmKgyRFQvDHCIiOqBPTRE1oUBDhFRPdTVQ8MAiMiyMMAhIjIADlERWRYGOERE1WrrhGEPDZF1YYBDRFTNGJ0we14ZjHXTBhjhlYmoNvbmrgARkSWrb8+NvnLBPi7wdXM0XIWIqF7Yg0NEVE1XjFLf3Br1cmMiWgIAHq3+l4hMjz04RETVDDVE9eaDXfFoREv0bOVtoFckooYyag9Obm4uxo8fDw8PD3h5eWHKlCm4detWrdeUlJRg2rRp8PX1hZubG0aPHo2srCzx/JEjRzBu3DgEBwfD2dkZnTt3xueff27MZhBRE9aYISp7Oxn6tvWFoz07yYnMxah/fePHj8fx48exdetWbNy4Ebt378YzzzxT6zUvv/wy/vrrL6xZswa7du3C1atX8cgjj4jnk5KS4O/vj59//hnHjx/H66+/jjlz5uCLL74wZlOIqAkw1kQpmdFemYj0MdoQ1cmTJ7F582YcOnQIkZGRAIAlS5ZgxIgR+OijjxAUFKR1TX5+PlasWIFVq1ZhyJAhAIDvv/8enTt3xoEDB9CvXz889dRTkmvatm2L+Ph4rF27FrGxscZqDhE1AVzKhsh2GK0HJz4+Hl5eXmJwAwDR0dGQy+U4ePCgzmuSkpJQXl6O6Oho8VhoaChatWqF+Ph4vd8rPz8fPj4+es+XlpaioKBA8kFE1BAd/N3MXQUiagCj9eBkZmbC31+6OZ29vT18fHyQmZmp9xpHR0d4eXlJjgcEBOi9Zv/+/fj111/x999/663LwoUL8dZbbzWsAUTU5OgaSFIdGx4WiDcf6ILwYC8T1oiIGqvBPTizZ8+GTCar9ePUqVPGqKuW1NRUPPTQQ5g/fz6GDRumt9ycOXOQn58vfmRkZJikfkRkO2QyGSYNaKN3ZhS3aiCyLA3uwZk5cyYmTZpUa5m2bdsiMDAQ2dnZkuMVFRXIzc1FYGCgzusCAwNRVlaGvLw8SS9OVlaW1jUnTpzA0KFD8cwzz+CNN96otT4KhQIKhaLWMkRExsJtHohMr8EBTrNmzdCsWbM6y0VFRSEvLw9JSUmIiIgAAGzfvh1KpRJ9+/bVeU1ERAQcHBwQFxeH0aNHAwDS0tKQnp6OqKgosdzx48cxZMgQTJw4EQsWLGhoE4iIDI5BDJFlMVqScefOnTF8+HBMnToVCQkJ2LdvH2JjY/H444+LM6iuXLmC0NBQJCQkAAA8PT0xZcoUzJgxAzt27EBSUhImT56MqKgo9OvXD0DVsNTgwYMxbNgwzJgxA5mZmcjMzEROTo6xmkJEdEc4fEVkekZdyXjlypWIjY3F0KFDIZfLMXr0aCxevFg8X15ejrS0NBQXF4vHPv30U7FsaWkpYmJi8OWXX4rnf//9d+Tk5ODnn3/Gzz//LB5v3bo1Ll68aMzmEFFTxJ4ZIqtk1ADHx8cHq1at0ns+JCQEgsajjZOTE5YuXYqlS5fqvObNN9/Em2++achqEhHpZ4DeFw5fEZke1xEnIiIim8MAh4ioWgtvZ+2D9d2LSq0gc26IzI+7iRMRVXtqQBtcyytBr9ZeePnXIw26NtjHGf3b+cJVYQ8nBzvJOQY8RKbHAIeIqJqTgx3eGRWGG7dKG3ytTCbDqqn9jFArImoMDlEREWmQGTgrmEnGRKbHAIeISIP67E4Z54kTWSUGOERERGRzGOAQEWlwVdSkJ7opmKpIZI34l0tEpMHJwQ7rpw2AAMDZ0a7O8kRkeRjgEBHpEB7sZe4qENEd4BAVERER2RwGOERERsaF/ohMjwEOERER2RwGOERERsaF/ohMjwEOERER2RwGOERERGRzGOAQERmZnbxmjMrdiatzEJkC/9KIiIzMwU6On6b0QXmlEl4ujuauDlGTwACHiMgE7urQzNxVIGpSOERFRERENocBDhEREdkcBjhERERkcxjgEBERkc1hgENEREQ2hwEOERER2RwGOERERGRzGOAQERGRzWGAQ0RERDaHAQ4RERHZHAY4REREZHMY4BAREZHNYYBDRERENqdJ7iYuCAIAoKCgwMw1ISIiovpSvW+r3sdr0yQDnMLCQgBAcHCwmWtCREREDVVYWAhPT89ay8iE+oRBNkapVOLq1atwd3eHTCYz6GsXFBQgODgYGRkZ8PDwMOhrWwK2z/rZehttvX2A7beR7bN+xmqjIAgoLCxEUFAQ5PLas2yaZA+OXC5Hy5Ytjfo9PDw8bPYXF2D7bIGtt9HW2wfYfhvZPutnjDbW1XOjwiRjIiIisjkMcIiIiMjmMMAxMIVCgfnz50OhUJi7KkbB9lk/W2+jrbcPsP02sn3WzxLa2CSTjImIiMi2sQeHiIiIbA4DHCIiIrI5DHCIiIjI5jDAISIiIpvDAMeAli5dipCQEDg5OaFv375ISEgwd5XqZeHChejduzfc3d3h7++PUaNGIS0tTVKmpKQE06ZNg6+vL9zc3DB69GhkZWVJyqSnp2PkyJFwcXGBv78/Zs2ahYqKClM2pV4WLVoEmUyGl156STxmC+27cuUKnnjiCfj6+sLZ2RndunVDYmKieF4QBMybNw/NmzeHs7MzoqOjcebMGclr5ObmYvz48fDw8ICXlxemTJmCW7dumbopWiorKzF37ly0adMGzs7OaNeuHd555x3JfjTW1r7du3fjgQceQFBQEGQyGdatWyc5b6j2HD16FHfddRecnJwQHByMDz74wNhNA1B7+8rLy/Hqq6+iW7ducHV1RVBQEJ588klcvXpV8hrW2j5Nzz77LGQyGT777DPJcUtuH1C/Np48eRIPPvggPD094erqit69eyM9PV08b9Z7q0AGsXr1asHR0VH47rvvhOPHjwtTp04VvLy8hKysLHNXrU4xMTHC999/L6SmpgopKSnCiBEjhFatWgm3bt0Syzz77LNCcHCwEBcXJyQmJgr9+vUT+vfvL56vqKgQwsLChOjoaOHw4cPCpk2bBD8/P2HOnDnmaJJeCQkJQkhIiNC9e3dh+vTp4nFrb19ubq7QunVrYdKkScLBgweF8+fPC1u2bBHOnj0rllm0aJHg6ekprFu3Tjhy5Ijw4IMPCm3atBFu374tlhk+fLgQHh4uHDhwQNizZ4/Qvn17Ydy4ceZoksSCBQsEX19fYePGjcKFCxeENWvWCG5ubsLnn38ulrG29m3atEl4/fXXhbVr1woAhD///FNy3hDtyc/PFwICAoTx48cLqampwi+//CI4OzsLX3/9tVnbl5eXJ0RHRwu//vqrcOrUKSE+Pl7o06ePEBERIXkNa22furVr1wrh4eFCUFCQ8Omnn0rOWXL7BKHuNp49e1bw8fERZs2aJSQnJwtnz54V1q9fL3nfM+e9lQGOgfTp00eYNm2a+HVlZaUQFBQkLFy40Iy1apzs7GwBgLBr1y5BEKpuRg4ODsKaNWvEMidPnhQACPHx8YIgVP0hyOVyITMzUyzz1VdfCR4eHkJpaalpG6BHYWGh0KFDB2Hr1q3CoEGDxADHFtr36quvCgMHDtR7XqlUCoGBgcKHH34oHsvLyxMUCoXwyy+/CIIgCCdOnBAACIcOHRLL/PPPP4JMJhOuXLlivMrXw8iRI4WnnnpKcuyRRx4Rxo8fLwiC9bdP883DUO358ssvBW9vb8nv6Kuvvip06tTJyC2Sqi0AUElISBAACJcuXRIEwTbad/nyZaFFixZCamqq0Lp1a0mAY03tEwTdbRw7dqzwxBNP6L3G3PdWDlEZQFlZGZKSkhAdHS0ek8vliI6ORnx8vBlr1jj5+fkAAB8fHwBAUlISysvLJe0LDQ1Fq1atxPbFx8ejW7duCAgIEMvExMSgoKAAx48fN2Ht9Zs2bRpGjhwpaQdgG+3bsGEDIiMjMWbMGPj7+6Nnz5745ptvxPMXLlxAZmampI2enp7o27evpI1eXl6IjIwUy0RHR0Mul+PgwYOma4wO/fv3R1xcHE6fPg0AOHLkCPbu3Yv77rsPgPW3T5Oh2hMfH4+7774bjo6OYpmYmBikpaXh5s2bJmpN/eTn50Mmk8HLywuA9bdPqVRiwoQJmDVrFrp27ap13hba9/fff6Njx46IiYmBv78/+vbtKxnGMve9lQGOAVy/fh2VlZWS/yAACAgIQGZmpplq1ThKpRIvvfQSBgwYgLCwMABAZmYmHB0dxRuPinr7MjMzdbZfdc7cVq9ejeTkZCxcuFDrnC207/z58/jqq6/QoUMHbNmyBc899xxefPFF/O9//wNQU8fafkczMzPh7+8vOW9vbw8fHx+zt3H27Nl4/PHHERoaCgcHB/Ts2RMvvfQSxo8fD8D626fJUO2x9N9blZKSErz66qsYN26cuDGjtbfv/fffh729PV588UWd5629fdnZ2bh16xYWLVqE4cOH499//8XDDz+MRx55BLt27RLraM57a5PcTZz0mzZtGlJTU7F3715zV8VgMjIyMH36dGzduhVOTk7mro5RKJVKREZG4r333gMA9OzZE6mpqVi2bBkmTpxo5trdud9++w0rV67EqlWr0LVrV6SkpOCll15CUFCQTbSvKSsvL8djjz0GQRDw1Vdfmbs6BpGUlITPP/8cycnJkMlk5q6OUSiVSgDAQw89hJdffhkA0KNHD+zfvx/Lli3DoEGDzFk9AOzBMQg/Pz/Y2dlpZYZnZWUhMDDQTLVquNjYWGzcuBE7duxAy5YtxeOBgYEoKytDXl6epLx6+wIDA3W2X3XOnJKSkpCdnY1evXrB3t4e9vb22LVrFxYvXgx7e3sEBARYdfsAoHnz5ujSpYvkWOfOncXZDKo61vY7GhgYiOzsbMn5iooK5Obmmr2Ns2bNEntxunXrhgkTJuDll18We+SsvX2aDNUeS/+9VQU3ly5dwtatW8XeG8C627dnzx5kZ2ejVatW4j3n0qVLmDlzJkJCQsT6WWv7gKr3PXt7+zrvO+a8tzLAMQBHR0dEREQgLi5OPKZUKhEXF4eoqCgz1qx+BEFAbGws/vzzT2zfvh1t2rSRnI+IiICDg4OkfWlpaUhPTxfbFxUVhWPHjkn+YFU3LM0/AFMbOnQojh07hpSUFPEjMjIS48ePFz+35vYBwIABA7Sm9p8+fRqtW7cGALRp0waBgYGSNhYUFODgwYOSNubl5SEpKUkss337diiVSvTt29cErdCvuLgYcrn0dmVnZyc+RVp7+zQZqj1RUVHYvXs3ysvLxTJbt25Fp06d4O3tbaLW6KYKbs6cOYNt27bB19dXct6a2zdhwgQcPXpUcs8JCgrCrFmzsGXLFgDW3T6g6n2vd+/etd53zP7ecUcpyiRavXq1oFAohB9++EE4ceKE8MwzzwheXl6SzHBL9dxzzwmenp7Czp07hWvXrokfxcXFYplnn31WaNWqlbB9+3YhMTFRiIqKEqKiosTzqql+w4YNE1JSUoTNmzcLzZo1s5hp1JrUZ1EJgvW3LyEhQbC3txcWLFggnDlzRli5cqXg4uIi/Pzzz2KZRYsWCV5eXsL69euFo0ePCg899JDOacc9e/YUDh48KOzdu1fo0KGDRUwTnzhxotCiRQtxmvjatWsFPz8/4ZVXXhHLWFv7CgsLhcOHDwuHDx8WAAiffPKJcPjwYXEWkSHak5eXJwQEBAgTJkwQUlNThdWrVwsuLi4mmWZcW/vKysqEBx98UGjZsqWQkpIiue+oz5yx1vbpojmLShAsu32CUHcb165dKzg4OAjLly8Xzpw5IyxZskSws7MT9uzZI76GOe+tDHAMaMmSJUKrVq0ER0dHoU+fPsKBAwfMXaV6AaDz4/vvvxfL3L59W3j++ecFb29vwcXFRXj44YeFa9euSV7n4sWLwn333Sc4OzsLfn5+wsyZM4Xy8nITt6Z+NAMcW2jfX3/9JYSFhQkKhUIIDQ0Vli9fLjmvVCqFuXPnCgEBAYJCoRCGDh0qpKWlScrcuHFDGDdunODm5iZ4eHgIkydPFgoLC03ZDJ0KCgqE6dOnC61atRKcnJyEtm3bCq+//rrkzdDa2rdjxw6df3cTJ04UBMFw7Tly5IgwcOBAQaFQCC1atBAWLVpk9vZduHBB731nx44dVt8+XXQFOJbcPkGoXxtXrFghtG/fXnBychLCw8OFdevWSV7DnPdWmSCoLQVKREREZAOYg0NEREQ2hwEOERER2RwGOERERGRzGOAQERGRzWGAQ0RERDaHAQ4RERHZHAY4REREZHMY4BAREZHNYYBDRERENocBDhEREdkcBjhERERkcxjgEBERkc35f6u/uJO3lAqaAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "show_waveform(yes_waveform, yes_sample_rate, 'yes')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Waveform: tensor([[0.0072, 0.0061, 0.0055,  ..., 0.0098, 0.0085, 0.0092]])\n",
      "Sample rate: 16000\n",
      "Labels: no \n",
      "\n",
      "Shape of transformed waveform: torch.Size([1, 1600])\n",
      "Sample rate: 1600.0\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "show_waveform(no_waveform, no_sample_rate, 'no')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 频谱图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "def show_spectrogram(waveform_classA, waveform_classB):\n",
    "    yes_spectrogram = torchaudio.transforms.Spectrogram()(waveform_classA)\n",
    "    print(\"\\nShape of yes spectrogram: {}\".format(yes_spectrogram.size()))\n",
    "\n",
    "    no_spectrogram = torchaudio.transforms.Spectrogram()(waveform_classB)\n",
    "    print(\"Shape of no spectrogram: {}\".format(no_spectrogram.size()))\n",
    "\n",
    "    plt.figure()\n",
    "    plt.subplot(1, 2, 1)\n",
    "    plt.title(\"Features of {}\".format('no'))\n",
    "    plt.imshow(yes_spectrogram.log2()[0, :, :].numpy(), cmap='viridis')\n",
    "\n",
    "    plt.subplot(1, 2, 2)\n",
    "    plt.title(\"Features of {}\".format('yes'))\n",
    "    plt.imshow(no_spectrogram.log2()[0, :, :].numpy(), cmap='viridis')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Shape of yes spectrogram: torch.Size([1, 201, 81])\n",
      "Shape of no spectrogram: torch.Size([1, 201, 81])\n"
     ]
    },
    {
     "data": {
      "image/png": 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p6U9/evqmb/qmNE3Twz6W98dUSverI+xsZzvb2c529iFq3ntuv/12/tSf+lP8i3/xLx7tw3nYtuvZ7mxnO9vZzh4z9u///b/n2rVrvPjFL360D+X9sl1mu7Od7WxnO/uQt1/+5V/m13/913n1q1/NlStXHjESkEfKdpntzna2s53t7EPevuu7vou/+lf/KlevXuVf/st/+Wgfzvttu8x2Zzvb2c52trNH2B7VzPY7v/M7ecpTnkLf93ziJ34i//N//s9H83B2trOdPQZst27s7LFoj5qz/eEf/mFe/vKX8/Vf//W84Q1v4OM+7uN4wQte8AC+0J3tbGc7K7ZbN3b2WLVHrYz8iZ/4iTznOc+pvJYxRu68806+8iu/kq/+6q9+r++NMfLud7+b/f39HVfuzj4gllLi9PSU22+/Ha13UIYPVfv9rBtl+93asbMPpD3cteNRYZCapolf+ZVf4RWveEV9TWvNp3/6p/OLv/iLD9h+HMdzFFrvete7+JiP+ZgPyrHu7PFl73jHOx41MYadvXd7f9cN2K0dO/vg2ftaOx4VZ3vfffcRQuDWW2899/qtt97Km970pgds/5rXvIZXvepVD3j9a37meTDf6CUaFdEq4aIhsolafTKEpIlJsQwdN90crSKaRKs9nQ4szEinPVYFGh3olUepSKMCLhlS0hyHnnVoueHmDLFhipaYFK0O+XM0cz1xuVtiEPWJmZnQJKZk6zFolWiUvEerSEyaiMKqgCZhVCQkzTq2AMSkWJiRy80ZMSl8srhkCKj6Xcv+AEKWKV6GjlM/ozcTczPRKk+jQ93WpY3iR0yKkDQ33IJjN+OtJ1c4GzusifTW8bGX3o1VgSk2WB1otafXDqsCc+3Off72frWKWBVIScvxJlPPgSHV73//7RsViEnl82oJKMYo33uMTf2cmJT85I6IVQGtEntmoFGBTnti0gxRbvVyX5Rr4qLh7evLnB0nfvrzv5/9/f0H3Gc7+9Cw93fdgIdeO/5/r/s4Lu5HGuUxJJaxY5UaGhVpCPK6ilgCCc1J7Os91itHrxwnsWdMli7vwyh55kO+1z0GTUITuRkWnMWeIzfHJcPt3VF9LpSKGCIBjc/PjiGh8v6mfL8fmBW9dszVRKM8loDH4JJlSoaIplcOTWRITT3WiGba2m+xkJ+FMVmMSnT4etwgz0h5XizhAe/1GE5DT68de2qs++uVw6jIEFscBpefb6NSPR+/OTyBt60v8/TF3dzWHGFUIuTnWBM51GtWqeNud4GZHtk3AyE9sBIR0fl8a1wy+GQYo6VREa0iY37un9bdw0yNtHmdCsg6Ws5TOW5FJFHWKluvZ6M8rQr1O7q8njfKszoLfNmnvOl9rh2PCW7kV7ziFedEw09OTrjzzjt5c3oKezltj6jsOD0+GVw06Hyz+ig3j0uaSVuWdGgljnYElipxpBJWRRZ2pMnv0yrSaS8XMRrQEBvFKXusfItTst/9ZgBgipagIk7vYfN7R+PQKrIOLT5pxmDF2WYHHZKi0RGrA0bJzazzTb3tGJyKrPVhPq7EOjTyYGa/ZlUgJs2J70BBpwNRK5zVOJVY5gdHk1iYEa1SPS+dFvL0gOaIPY7SDDXvaRpLYyJaG87aC2gV8dHgk8ZHTY9nYSYJUu7nxCUoMLTaM9cTY7SMsanXpFgJNMp3mBmHj/nBwdQHEEAbee86NMSkmaLB5nNXjqvVEiwt88NWrmU0D3xQQ1LEpHFxD9/Jse9Kix9e9lBrx43uCmdNmwMyxyq2jLGh0w5Dyv/PwXsy3Of2GaPlLHQcmIFbmxNOgzjbYp3yNNrX5yBmpwswRnledduik+GmFvJ8H7cDze0gfOPYSnDq1B69dqz1hEvi6OZmpFfiJGPS9bjLPrSayt4BSGyev5AsAU1KCg+0egQ0PjY0KsjzniShiPl4WiXCBENsCGhs0ihlmVRLQJIJ8noy5fe6GizLfud6RJuePWtYtRe4ZnrmesrOUdYIa5asYsfKHBC1w2vHGJuaSAD1XJ0FWc/neuIsdFx3Cw7swNxMDDlQubvR9TsVK9d3jA0umboObs67fFZJEly0NaCS86c5Cx1nROBN73PteFSc7ZUrVzDGcM8995x7/Z577nlQPciu6+i67gGv/8o7nsjhLfLvlBSz1jFvHC4YfNT1ho1JkYAQ5WZISdFaT2sCg7f4YBicJSXFhfkarRLLqcHoxKKdcMEwBcNhP7DfDLz77JDV1BCjRutI3JOHYe0apryvvvH01jOzjsYEzqYOFzXrSS6+0YkQFS4Y9vqRw27ARUOImsZIhtuYgFWR1niG0HA0zOispzOepWtxwci22XmPwXLvyR5aJ/b6kd56Fs3E2jeM3nI6dMSkuDhfY3QkJYXRkZl18mCSuG+94HTomHcTi3Zz873z7AIASiXOxo7js56+dyy6iUZHGhO2AghxxoO39NZzsVtxPM1YTi2LdqIzHhdN3SbliLU1gUv9iuOp53jd46Mm5sVIKflORiWmYAhRMbqGWes46AcGb5m8pbW+Rsnl2huV6nmSIENvzrNKjN4yuYmdfWjb+7tuwEOvHf/39A6Ww6EEg9bl4FBjlQRvnd4szOvQcM/qgJOp4+bpnIv7K556cIMhWKZoOZvkuTroBlrtudiu69pTAuyFlaC0VHLeubrAEBqWriXl6szMOg679bl1C6DNxzJFiyax3wxcG/b4neOL3Lp3xlP2btT7XT5DHE+jw7kAoFSSZN+aVWxxyWyqaWhi0jVbLUGIi5YxZ3L7RhKLG35BowKX7LLuJyQJkrcz/JgUAc0YLTemOXt24lKzxCXDhWbFe4YD3uqvcFt/SqcdR26OVolL7ZIxWo6daPFqEqe+YwpWqpIqMbcTPhquDXss7MRT9q7z7vUh7zo75Nb5KZe7VQ7MFb/DJbnG2S+0OrDfDFxo1hy5GUvf1XNTM/Ct63Dseu5b79GYgFGR1kjl7R1HFxhOHqj09GD2qDjbtm151rOexc/8zM/wOZ/zOYAAF37mZ37m/VJcCN4wTDmzzQtoiJqzocM5Q9c5bHYqISm8NyiV0Dox+lxWUQmtI84ZYtCcaomSRmdRKrEaW1KS/RsdMSqymhrGUZym1pqVa9AqEaJmcJb1qiPNxAFPQT5n8uJIJ2fz+6Ics88RZ1I5GBBHrFVCqVQdhQuG0VsGL+8/XfW4ybJYDHSNpzFBPnvZoY3cJINuWDcNLojTWi57opObrWskQi1OcgyWtWsIUWNNYJgaBqjbraYGBcxax+QNJEUImtFZgom4qGl0riDk6+CDRM1W9yynluUoZfFgxRmHpDhezghBE4Om7RxGR47XPWfLHm0ixkRC3s+RN6QEbrIoBdqIczc6cnQ2Y1q19HsjXeMla42acWhQOtL3ci90jWc5toxjw2Im2167uY8/fngPzM4ePftArRsAK99gW3F8J05aUTEperO5D2JquDHO5bmNhs4Erhws2WulB+yTwQVDZzxKpVrNiSjGYDmaZvk+10ztmv1mxKpN1mmVBLoxSTvIaHEig2+Y4qYVs9eMWKWYgmGKlvesDgDY7yba/OwWu9CsmeuJ/dpGcbTKo3NGG9EMsSEiWXDH5vsaIiiYm7GWjBsVJCmOENWmXdWokB30JpsrFaqSfZ74njFabk5zuX46EJJkiUduxqnr6/d0SeNCx2/cvJWUFJdmK1odaM1G4m8IkswUJ77ysp4U537sZkzBovK2N6cZvZHg48Ywl2AgiA9odWAIVoIL37HyLTZ/t5v5ms+sk21NwEed12NxtMUSEOPDq4Y9amXkl7/85XzJl3wJz372s/mET/gEvv3bv53lcslLX/rSh72PFHR1eiQlTjEpVic9aTCEA421uaQTFX60KJOwTSAGTQyKbuboGo93lugVa9WglDjylCAFBTlqXDaezgTGscGNFm0SUSWGqUHlKGgcG/zKMqqE1ZHJG2LUsq+k8FPuh5hEjIq05WzLRVMqoRSkBEqJM5GLqolRnNx01KFXhuVVCLMpBwyWtLQEkxhUQunIepTvAxBOG9SoWfdNLU2lpHDWn8tW563jdGpqcAKwWnUo5ObyXsrEIWgmZfFRHjNrAlrB6A0pVxBK9ryaGsZBgpJSXfBBM6xaktPgNKE3nHWO1dDilg1m7lFKPi8FRfQavEatDMkm0sHEBKx1w3jcY29aBiDMdL2+6aQlmUTYM9hGHprlaU9cyn3joybd22Nv7MrHjwX7QKwbAGvfcClXjE4nyXxL5QOorZJryz1CVMxbx6KZeNL+ibQ+cpY0RcNhO2B14Mx1GfugWPmG+1aLGkCDrE1z62pm1hppvxTHYbU4jSFItmx1rI4h6sAULUvX8p6bB8z7iScdHtFbh0u6ljz3zcChWXPJntEoX/unhsSUSn/XEpJirgXHMeVSeEwKQ6wVqoqFUAGjN843oOhzydXFB3chMSmWvuPUd7zj9AKNjjxp/yYxn9djN+Oe1T6LZqLNuIqlb7nn2iEpKE4POuad45bFWd1nqYaVpMDoiNWRS7MVAMdTz5DbdGMQPEY/O6XRUlkcvcWHjO0wkSkatEqsfFvbewB3Hx0QvKbrpSq51031s6yOtNrjM1YmpY1/eF/2qDnbL/zCL+TatWt83dd9HXfffTcf//Efz0/+5E8+APzwXu3EwiEST2UHBWA7TzCRpgk1M4pRw2lDtAk3U6DEqXln5O9eHJ9PDeiEbWWhV212ilFjcgkyRQUJbOMl47q2h7KJbiGlSDP3KC3ZcXEmZiYRlrxXEWJC6YRu5WEbsiMiZ94xKtxxByYxv7jGe4NbN9jO088mXNcQo6K1Aa0jRiVM69BXI9bEWnLdLoWcdRM+6lr6LaXk5SQR4mI20beO3nqMjsTcTwY5VykprImMQAiloqBwriElsFacc/lbCRhC6ohR07SecbIMY0Pb+s1+83VLTnPjaFEDkOg1nty/aiK2DbK/mZFroxIkxXrdgkqEWQSdZBuvISpSK68pLce1WvagQC8c1kpcHvsI8x2R2mPBPiDrBtCZwBA6piCBoYuS9VgV0TYxBCmbzhpX21A+aaZomYJh5VsG3+CjlvIzoQaSJ9MMn/S5FpSPmiHkaljeDsDqTUm0LOS98YQm4xRITNEwRcPZ1BGSYjEbaW1g6VsiimhU3V8BTi5jh6HBaVvBPSeh5zTOOAs9Q2wYtRxPSBqjInM9sYot90777NmRK/as9oJPQ09E0eWerUuGM9/xjvVFDpuB2/sjXDS4ZJibiV4HrnRn7DcD+3asAUHMmW357lK2j7lEbFjsS5n6yt4Sm9eglBQRCW5SUswaVysDRscM3LQcrRd01nPQDfV8TFESg712lHbe2KFUYt5IsHBznLNyDaOzHM4GWh3oW0dsFJcWq9pm0mlzjovF3LrUsw/hMnKxr/iKr/h9CfXqSQOpZl/FjI0onTAmonUuQ0aFHhTJKqIxYCMYcRoqSpZMVJLJ2oTu5f3FWYcgnxPSJpoxRkrB+sySbMK3AZ2dfIwK7wxpNOAUqVMkTXW24u0j1gSCN0SnoZFINpL3u5QMLh5q+Q6DITaRzgbWbcAHhbUBqyNGJ4yOXJivaXVg0YznepQAl3r5fyndtDqw9g0nQ4fRiXk30ZpAZ6QvXKxkpylH8yEqtLa5vC4Zbq0AqESMGoUAmlKSYy/nchobgtO1nF/6tagkpapVviWVVBWiUtg21vfLtXbEqGvpPwbZR2pycJHydYwK8r2gcxAQR4PuArYN6BytYyOxPQ/c2tmHrv1+1w0Aq4O0O3JG6DLWYmoNHZ4xWELUdNZL5umainwfQsPgG1zGgMAGxBSTYu2l0lWwEGXNcHHjZPRW/xTOZ9U2g/yKowlRQISlJTVrJHB3QfqjVgUBX5FyiVVvwIgRglIYnRhSWx2tS+Zc+VMn6fO6ZLg27QFwxZ5VkJdL4kjRGwDnOrbcu9qHOdza6QqQ0gjQa98M7Bu40pxxGnretb4gwUFFJ8ea5U9BkMQlSbjYrQRZ7C2+9H7zOja3jtaEWvYta9zaWRoT6I2rgMmYFB5dy8lr12B0pDOeKRoGbxmmRtp8nQYdaKwETtvHIFn/xkrJvLce1TwGnO3v18Ilh05NvinJWaGUY2PQDL6UbANKQZwlkklgkjhWr0k2okwClxfnPqBtzFmZ9HnF2WqGqSElJWVeG3GTlRKxkf0mIAZNCBAnQ3Ia1Qb0PGFsEEc75EvWB0iIQ/aa5BU0YKyUuAHioQcl2xgT6a8u2Z8N3DJfcstCxoAudGuJxpVkt632tcHvkq7ljoK8jUnR1jJY7l/YTdnIBektl55xcYZGR3GIQGsDqZvkJp2slHejwo1GzmFCHspejl9rqTpYE/Eriz6zTEpK6eY9gp4Ot43Sa1aJMFgYNGqyJMDtO1LrMRmNnPL1ljJ7QhtIg6E51kw2yn6iAq9QzpCaCJ1UKlAS8ARvcEoCqu5gJJjNLObOPvytLN5GRRbdxOnYsjzrubxYcblb0hvJaK2OAnr0FhcM14cFIM9DCfKLk1z7TXvGZqRrZ2SE6HgU0N9+PzKzjv1Wsq+3H19icJbVsmc2H7nj8BiQe/zmMGN0lv1+xOrILC/qKSkaE1jYiSFYjqcZ+83I3EplLaAoAy0BTa8SF8ySy+YM2geeizIW5PIY0VO7a/TKsa/X9bXrZo8hNTUrdcnQdIHZZQF+9drR48BQEd0FDBaSpteOg2bIPVsBou01I60OtZROhFvmy3x9NFYFbBMYQsPaNxXQeKVf0mnPe9YH9Rr1xvO0S/ehSVgdOJlmuGBqMHQ8Sl/+sBtoTMjgKqlUuGDE2WaQ3MVeAKQX2zVjtPW6lkBq7RsaLcfSWY+y/oEn9UHsMe1sTRuApvZWo9bEmCTbKc40AZ2UFpOWxVyyKAVBgVagEwSFiiqXHGX/MeYSRs7cQtC4DAJSWjK4GKQkLQ1NKTellDPYoCSrMkEcFwrltrZHtksxO/r7mW7FCaakKsL4oB05aAYaLUjlmZkedFwAgNDWmbn7W0yKKZpzUPqUFD5t+sZlfyr/Xs+7SpiclaagpOca8vksmyWIzqBMJOVyckz5nHiIQRGBxkPScj61jmgTidqc31cu48eoUCoHU7VCAEpLBK+8qtdAjkGhvCJpeX8JyIiKmGQcSGsl7Ybu4T0wO/vwMJ8k8+m0pzUenQEJVkdmpvQjTXYYqsKAyuKtMyZD5kY3rZoQdQXuFUSrNhkbETYLutVRStBB45wlDIZRN5zOOsnadCREVXvAFuo8/xRNBupIdlYyPp0BPIZEo3yeZY+1d9srT68CTd4m5CDcoXFJs0wtMWku6BWNEgRzcbCDbihTQzFt+rhNKzwEQx7rabbmWFehO8cBUHqdY+Yn8NHQG1/bXVbHOgc7BVNf88nUsrFSiU5L5a2AUkGqAYfNOmf1kmD4pOsxu7y/znpa7be4EVIOnKgOtWtkG6tDHZdEba5vTEoSnAyYLT3u92WPaWcbnCBn/WjhpCH0EeaKMBhwGuUVKkHIjk+vNalLqIUnBrNZiJXGLA06QLggznEaLClo0qTBJFQTpb/rDcaKo5vWDcnr2iuOQdVs0HQBPXO4dUNcW8yek9LzIJlwyOAnIAcAiuhlJk3rVHw3KSriKCNGrQnstwNXurM6I1YeKKCWcVwS1OLRNOPGOK89D9jcMC5qTtYS7VkdCRnwFEqgEmUJKX3vrnE0JtJbn8eopEweB0tzn8UuFeOVSOwiNFEc3dqQrII9AaC5yaK6SLAJJum/uCeO4s2DjAio3HNVUZFmAdUFVF6shlUrwcnaSo++iygjmWza94xdRDVRSshaKhhJJ5TThPs6UpOgi6RRo4LCK9DaYUyNfXb2OLHrqzm9MbmEabl175TL8yV3zI+Z6UlKvppa+u2sEMIctAMr33I2dWgTpOKTrQBoOpMXdBMEQRwaeuuhz7d6lMxu1jiecuEGQ2g42e85Ws1497susXdpxe0HJzxh/1RKnzmz6qyX0R894KPhzAmI6srsTEYDpxmHB2ue2F7nQA/VYfbKcUFPNCQaVUfzcSQCKQOhzhNWNEBLxBFxGI7CnOMwr9sMW8Qy94wHvP3sEk+YH3Nrd8o6tIzR8n9v3EZKimff8g5mZpJ5eyxjtNyz3ufe0z2efPEmT5idsG/HfByqjjG12rNnJ2bGMbeT9MiTrmOKt/RnwlOQS9GNiqyjrH1r37ByDZdnK3ojQCeAuZ1yK0AqAjdWM7SCeTcRMvjqltkZC7sZBTQ6EqOpI1oAM+vYa6Qa5sLDGxt8TDtbZaTvV2Gyidq/QyXJmFLOGqOS3mxxcipnunVnOfPMJc9U+pA52wXJnhOglJZsqlgCIqTsQIgQ+4B+kJJNtAlyJlePGwTY4zXJA22Q7Lr8rWTjWxbQhPydC/tMTMKy5KNhHRpOXM/Z1NW50lL6kihbM0358re+IofPnd+tf2/faBW0kEu1KEh204qWMn25Jqpm+iln+qpJpFzitzl7d8uGFBPJiKMuzlLbRHSC6FQ5+CACSknpHU3S0pdNTblOulYKUpNQkc3xlIw5/x6jYhwa4vrhRac7+/CwAoqKTpxGo0Pt6wGMedEuqOMC5NkGHK5dw5qGvXY8Nw4if9cIvI9zvdqEIOC3AVJtCiyaiVN9fh5YsqvI6dTJKJ3RFTTkk2btGxbNtJkdL73QnNkaEu0W81Pc+gkJhqRrVhtQdSRIMl5N0DImVErJ5xjn8jYuVwiAmrW6pKtTjGz6m40OG3BUQWRnIqIxWmJmxJui4XicsWhG9qww8FkV5e9B1rZihQjIJ83oO6ZoWfm24lTWGcRWerwle1154SkAqdoZHfGhpC1CeDNFe26sSqkkU1AFsJW0sGzdb918KHtMO9u9/QHsjNgE3MzIAh0VqomoLlUAjF9Ztl1HiqBsPOdswzyiosLmi1cQx5jsFOMGdOO9Bp0wbSSqCGcWMyrUqUE7MKNivGhwFzzKRLC5FKsj/pKT3nITJWt1OTO2EU4a9KAJBwqaJO9VYLsgoKt8Ayx9x9K3FeZeXnfBcJbJLpwXBKT3hnHdkCaNnXuMDRu085gh/0FjbKBrN6VUa0Kd9wVqucZFjc/oyjgY7KnBXfT4WZByMtTvlsY81uS1/M0rmHuMjfhGQ0poEwneoE8zyKwENl0UIFPjmW7MsWuNv+DlevRR+rFrQ2pk/EocbHa0Sa4XKmEOp3rl/WhQS5uDg4RK0rtV7+lRxzvxgceTddZzPOzXas68nzicDfRWSsi/e3qJwVv2uxFT5mFRnEw9YxAnfM+NA/yy4cLVUw5nQ923oPgDvXWsfMvx0Od59sjKCe7jzHdM0XA69Rk0pJh3E+kyLLqpAoliSpwMXS1Bm+wYpmBYjS3MoTeOs0nQvIVgYkgNDZkMIxmGYGsftZSGr/kDpmRYaMnMTmN/jvrQJVPfs8rUsaehPwcGG6NlYSY+Yv8+YtKsQ0unPbNmzSddfVs9J4Udq1GBmZl40t5Nbp2f8IT+hH0z8Kaz2zhzsq4dDz3X7j6kPxiZ37EBH52MPSdDh08yA9sbV4/jzHVcX0k/XSnhJuhM4F03DgnecNdt12gbGfUaveXGek5nPVfmK6Yo89JTghikYjAFy9Kfz5ZK6V/nYzkaZhLoLB8e3uMx7Wx90PihEYCOSeczwMQm+9Tkv+U3FjBw6ZtmQE/KUYoKqtb6MZuslpLpFoecNtukqNBB+o9+nj9r1KQ+oW0k5PnaMoYC2aF7nXvJCqXFCdTjTZL6Sh9Ysuq1b7g+zpmirdFsATa5qOUB5Hz/VmkBcGkTsVZ6DUBG90qZpMuMV8UKGAGoTE8hM2C5YCQrjkqO3cp3jKX/XJxd/h6pnM+c6Zbrs1W5EqS2kaqC0lKVgNw3t4nYpM1+zf160xXRDIT7/U7uN6uE2lbkSDJqlIKSMvRj+knY2ftrMakt8J6QLRyve+bNhFWR5dQyOCtjJjrVEZIx2DrOY5tAnMmzdzJ0zFonj30wNFpK1IWswmTAYUH1j94yKcMYhDynM55GmzprO3qhBrRJy3ifygx42bmU3mGIutKugpR3j8Kca/6ARnluawRwtc3vCxteZKPu9yxlM8Rz1ISddugUK1NU4W+PSRHyJIEjZ/SZ67lksaVnWygeGxWI2tfPKcjsyldvAu2ejCEOW/Ov25U1HzVemYpm1ipht6oLk7es8hSE1oLSHjKb1BQNPmhMXg/kHGrp2+tYZ3SP1jOUSvTWPwAwWjLkKRicf3iTDI/pJWYaGhikF6dmMtuqNESvcrYWN7OspVORF3MSJAoYKK/7ChnBAXGsJmG6QJg0TNLjJShSE9E2VoeRugho9KnCLxLxsoMziz0x+IxU5kTqrOryKCMviANXkyYpcbDJRlILqg0CwPIahYB+YlRM3jI4y/U0p2sEWLDKzk9AQxo3WYwNXNxfoby83nae1ML+fKx0ho0JXOxWddatyeICBZa/mdsTxN49q32WU8vZsid4GaEhKmKfUEbOpGTiiuhMRiRnB+k2Tq6Qe5DLwTHIGFDqQy4bS881JZ3bAgY198ROw6TFmeoHWSBUkgsYJFhKXaxBUNSChFY6EbVktCopWAsoLs4j8WEiCnf24WE+amwjM+mzxnFjOefsrKPJyPzjs57gDGG+JurI6FpcZojzGbF/YW9Ff8HzruuHrJct6sISoxPLoUVrGTNpra8znQDzPLd75lpxGsHQWc/lXlC4U953QccalbjYrwGEJCPoSvUKUu4ccqlTq8RZ6HiPu8D/Ob6d1gSedfg7FGrGPTOwrwf2zUCvHHO9ycgimrkeiUkzpEbQxdpVIowmhprpFhNyi4bT0OOjyY5bOOEbFXjncAEfDVf7U0yKrFOTM1tXKRyLdTrg87jhfjvwpP2bMlvsuvNjUVsTCcKNrmiVlznleayO+HdvXGR90nPl6gkH/SAlfyeI5imYyiQ1WmHlG50VYJSR6oMPhhtHC7RO7O+tsUYoaRVs5n+B5dgyrR/ePfeYdrbRa1Sbe3xnDXEWaGaOmAUCvDPnopHScog+lxq3st32usGsFes7pVeoBgM2EZu46f/ZBE1Et6EyQEmJWbKy6UKUvmHOvmKXNv3eTo4zjUayzEZGjlIbz2V4NeMqCaCS4MFFy01vaBoZuk5JMuzWSrl3NTaEoAiToCEX7cRhd348oQzOF5TkLIskbLhAYxVxKECFEjUvGik1rboWbzReQ1gpmSH2iqA02krpO2lxcikJ45MecvauM2p8C2kcU0YV5yxeZmTFscYxX7CSyUY21Ymo0KOqIG6pFiSSzgjEXIWISq5z9Jq0sthTQ+ySzNV2ORBSgH/wCH9nH75mTazkLSqjhiFnkMEQvVCKumBYuUbQwYW5aKvy03UeV9D5CeadONeYNoDEYj4DD41K9acxIqThooyg+KirUzXWb7VyMnDIBLwSop5C9SiMVCGjjwO39GcVdWxUEK7krIglCGQhvyjOs/Rsh9RyHGYcmnVW3tLnerWiNHbebcz1JEDKnAkXUYEiSHJgpcRekMmddrhkWNLVkrVWAixbZADTMmwqdIW20edzP3jLOjUs2okQI7aRAMmqIKpBW5Wvwj+/dhatqONTs8z7Xsr6Bei2yVwzzkSnyp5VEM3lOEB4GoJ78ImPB9xvD2urD1FLk0ZfDLKInmicSei9iMrgpjTIraQyYUEySbJIJz1XZTYl3fm7Ff3NyHjFEPuIXSliA6HXG1BNK462ECI4ZzYkFTqhLzthopqMONtZQFkpP6i5l4u3suJbyjzo3Ff2qlqm9tmDNFL+TEnmcNWkGQ8cTeNr32TWiONdjQ0pipNKneZyv+Riu+K27qT2SgqAYhvcAHlBKIodeQg+RFMHwwEOmgGrIsPMMnnDaCMrp2EtVIspKPTBlEd3VOV9VkFhVorYKEEql1GhXFKugQ9swFT5u+pRob3C70XpseYxqwQCDBsUyciDoY1UNUJGdqsC3EpF7QTMmaE9VkwHEDvQC0/TeqZ18+DZ8s4+bE2pRLNVzdAq1fbKFA3RS4ungGiKgIiUfCOLdqqOdNY6Wuuz80tcmq/xUXMyCLDJqVRjRCFIgAuzofIkK5Xwmbd3dLbO9neNJxpVwUFlxn/WOEZvcWFTBi10gqU3+uT+hoylbHEZSxnZCz9y0ugUaxk5JMUqdpzGnrvHQ2KruWCWTLlsHCiYDRElKA5+ric6M1bUc69d5WHe10N937YSUas8q9Bxg8V5RikVubU7YYyW05VQX7a5970wU+WNPlpdZHQWkyc0mmirYAtI8KRzVc3nyYvRCdGInknJ3s4iZ1PL2dDRmEBrg3Drp81ECXltV1vBjsvthFkrPO4yofI4GP0hSr8tdAG/UGDjho3Ja/TKSKmyyAwqGSlhkOwyaSk/a5NY3Z4YL2jizIFJhF5L37CMkTTZYWc2qRRLTzWbztSDwVTmp2QSadQkpVFTzriaVMurpeebvDgsYj6+fKxJxQ1y2SToJBse1i0xz+jNW4G1X95bwR6YWyIXuxV/YP/uWjYCctkmD6UnTUCkqQrIocynHU1zlq7ldOxwXiJtYyIfeek+QGjuCqfy1HncfHMO/GRAmUq3qBrJcp3VKK8rclmZVB1uAZ2pSbElLSmXt03EBum/Twq7kqzAWzl/oReksb7ZEPcCZuEle9ZJzmMBuOWsOiRw3hB7ea2wUtU5q509biwlVYcBQs5sCheuVonZ3oj3pmaVfeMlyJyEpagxgbVrzknkjc5mUKYo92xnRKIWk+pnb4uXKJVodGSZ+chTXgN81EzBsPbCerTXSXWptHiMTkxegFKSbYuUp7OZrB9VaRYBbro5R27OpXbJoV0/QHJO9q05sCJiMMSGhZ7o9VnVb5XSsmUV23PzvG0eM2qUz9uqCsQyJIbY8O7xAgs7cmtzkiXtfJbeFD3dRgk5hkuCRo6oyjLVai3o7CbSt65SLmoSJ6MA0C7qgjaWAMjtGc6O5pz6BWbusTZw5tpaTaj/16lWNwAGZwlBSwVTx9zfTTQmssp4lTYz9/WzCe0fBwxSIOo5ySL8tqW0W+ZqBxn3ifMNqKk6tChl5RQVykamSwG1r6DN7FFt2V5KwjrPb5aRoKjVBiAFGYAj5ApmUISOnFnJ+JE5y/D4C0HGfEoJOn+G8gVElI9Vb/aLlhKXNkGcrDM1I5+1omZzsVsxt44nzW6wZ0Zub2/WaHMZW4HuK4POWW1EsQ5Nhbf7pJmCoPROho71qiN4mTNWTWS6YAWmbzxgCVbYXUKn5ZwUUYUEeC2I6y6Bjeje45YN2klWr0wkYWSWNjtb7aS3um0pZ/ZqkvNjBkVSELLTjl1CD5pmDVO3RVpRmvAKqWBYYfyKUSoVsZV7pVB67mxnNlOBFoKFRT8R4mYBbq2XMnJWoGp0YI0oaun8HHtnquYyUJ1pTNAYzpUqpzz65ktp0kQmb2X/+f0loJ6ioQXmzSTgqtyjNbmXPE7i5K0NefSmqG9totcyD/uu5SHjwuI6k8u9m9GVuZExm3nOVF2y9PqMy3rJkBqmZKozbZXM6It0X3aIKqAR1ihHU4P7RgXOQse71wdcbNeVFnK7bdVkGcFKBenl2Dsr+uQ+GmbGYY2rQM7OSIVvOTX0jcI3uVKHzCTP+4nj+2bYpSbYLBrjRKO7KCy1NpwjKikCK2EbXBU1RoeqIOe9SHxqlSTZ6R8Hc7a0kZTsZrYz5QV/KzsE0CstGU/epsxpYhJpMrioNhnllPulWpyc6vID4jcCBA/oJYKMBI02o4upFI4AKSX8ZX+uR5ycrvO/kI/NAjmbrdtGRZqkvBFSAzah2kDfOS4tVlzul/TGc6ldMjOOK80ZnXa5bKxYppYbYY9jP+ee6YB1aOoM2bX1HoO3rMY2IyUT16/vwVGLvbrmQgZ8WCPgqYLIK5JiY2PxzuBWFjVq0kLK5ilK3zqcNNBGzN6Esqk6ObkoAhKrgZETRxpdvlalBG8iybWoCG6R6nlJOgm3tQ2EPcBKtqxGg3JKgi+9FbSA7LfNr2XkdAjSy1Vnuznbx5OFtOmdtlnCMmhVyStaE5iQyo5W4mxbG5jNJiGfV8Ju1BhRtApB03Ze1LcyTaBSknmuh4Y4m1DdRGs91uRnPgOkQlKMQ1sJZdrO07dOMltvubGcY3Rknj9XZ1RzGSdynYzjxQTXhj2WvuXasEdnPB+5f60Clp40u8EdsyMOzZo+rxGltwqS1XbaccGsuGzOuMWcMleeXkXeEQwubUZhllFmgsuMv0smg6/WXA97rGLLfW6PmBS3dcdcbJY88/DdtWd7FjqO3IyZccyMOCutEmMeC7g6P61OcIqWa8Met/RnLLbAUnLMGSgWdeWk3swdK7qrK1KCvhFn2VrJaLd5AwrwSWJ1JUIEUbNct5U/2gdNTFZY7Ngw6im1YRB7X/bYdraltl6Qr+TSbCnPavFdMspTUp2tt0dFClBX5FpOTNWBq4KOdfpcJiqjLRtEcuFariNDxWHnj9W9l57iaPJk+QaRi2bjGNTW/+s2ORjwSkrLSviJF83E3E7s2Yk9M9aHqjhalyxDajj2c058z41pzsq3FbG3nFpGZ1mPDcZIGSo5jR0VxkYO+pHeusqMU+frEOq4SuEYMwI4X5Ma5Ax6w0K5la2n3ON+kMspZXsl56SwQwUl5zDmEnwqn5EDImoQJedIFb95/89QaTNbncErMWamMbcrIz+erCy2CuhyxkLUG4rF/OOikfuN3K9tPE1+FsprIn2paRtRyyqlZa0KX7qpi7/JJWMJnuWZKZlUKR8LY5vHj23Wci7jLqFmZIW+UNtEkxRDzqKl39xJG8huuIGNiuxnFqcymlP6uaWfOtBgiCz0yL5ec0lPNApapTAh1v3Eoo2bZE10yTDGhl45igjCKnTViZssTDBvTur7Cl2jsVPOoks2LscsTE9CjjEEQRJPrWGWr9u2wy1iDYJOLrQd8vr+fMDoeI7SUo5Bzn0RGChZbcl2faAqi5XtSuntHKHR+2GPaWerjxtibElNRM2E2H+7PBtnUjoE0E7RXdOEPjFdDigvZeYwT5IVdXLjqab08NhkoZP0YeMioGe+ZrZKywxpe90QLfjLKZc7IcxA9SGPI8nDEaNGnQrVYFqEysksTj1tZnkDOVLITqWJ8quJ2CbSdq7KTMWkGYPlTMnNvS3gfBY6bkxzUSkJDTfWc0Zva/TXW8+scVzdO2NmHQftmuFKwxQsF7tV5YgNSXHsZhTS7zpj5i3urJXy/SKgbD7Z2XmZQYGSsnfK9JmJDPZqYw1WUlS4fC70mZVSf1CEQwVzT+oiwarNLDXUsazCTJWcAFowiaiRz4parq2GWuvLIgXKacJgBdi11qhx52wfT7aeGtzQ0lpflX2KXJ5Jm8W0BJTT1nPjouZk7EWpJmi6xkEjZV+gqvyE7IQ3ABuNyT1hl8d7zo7moBOzhYzhNEh5ePKGcbQEb1jsDZVuUNDHAvqBTfxvVMKYwIV2zcJOPGF2TKMil5ulOLotQXiXDA7DKnaVw9glw1noOLRr5npkrkacWdfsZV9PoomLISbNfreW2dWUWacyCxVQA/47upsYEntmqHO7IWkGmspvvG9lFOmmm9djiElX6sWTqWftGxJwOsmIUZkxdkHYptZjW9tBs8ZVRq/YijpQwZiU81cCrcFZhqFhbz5y0I9MuSLRmoCxnoPFwOQNw9hgrUyBdI0441J+Tkmd45d/b/aYdrbq/gFGRZDlX81WNhUeuJjWc1QyLUXthcr8J5mVCsl80ubvkO/D+wsI1DEWMrn+Zhg6pS2uCp3/kdiUOu8vSJAzusrkrySqMkYc3ugtZ3QMWkAG58d4EkvfClNNMLVsVthVjEpyU2rP3DpmxnFg1+fQg1oloWOLZhPxkyrjDVDPWyX6KOc/ZUlBhTjBlAkwSl+azbwz5LGqXOJXRWCo9HTJ+y/ONiqUytGoyjSTIfe9y3lDSkKpotDYHG85xqCIGBFVeHjo/Z19mNg0WGIjDrSwM5UFHKhl4LIw+ygOrWs8UxYhL060yf3eKYOby3uEYlSwHPeXAS30qGmrL6zut5QodX69KdsVFPTorLR48mywVKCCMDhlgRKjNuQURes2bjmHMpVQxnRcFCc8pIYhGYzyRKDPwgMuaZlWyPsxKZNbKM31sMcNL/J8+2ZgrseKiC7lZvny57+nKPXEnJ0KuCqSeZKzhm3IgVCRB93ObCuK3AuBSMmOtysU5VqWDLeMURV1txK8lH1rlQgm5Gu4cZNGb0qnCXBB1329L3tMO9vYJvSBsLbUrLCAdBLnkL/RJIaruZo5amIXJbvMRBWlFF2UbPRxI4jiPY/yGjNBCFsKPVHBWi78dIvfOByTiK30a1XaPFS1fLzvBfBUssBGesAp9xpVVBXspXtP9FqORSdSqwk6YdTE8VqIy4svCUETg8aPFt1E5osBoxLWyExgoyNPWJwwtxMXmjWd9jXyBOrDU7QuV1H4RdehEWerRDbM2okz33E2dez1I91Vx2ro8M7g1zaXcSUL9Ze9ONBBRqGYBVgbIfLoYuWhKL1pEFCU9LxzKWhls5oP0EnfOzkpufmCfJ40etQop/L7M0+yyvcAgiKvDjsvimqQMljYlyh4Z48je+eM6U4RFlFINml04nQQhH7RVfVRM44Wd9KhZ57Ll844Pp3hjjq6y2su7q/YayeMipwp4SEfnSyrKvd1de+k/Gw2AvNlntb2fuPUowTkupVjOVjIJMFyaPHeMGtWFO3Xk2XPdG2OOpjY2x9E9tJuSGk6LdJ+Q2wYEOIJl87zCu+ZcaMUtDUm9M7pEgALPeL0mn3tuNVoemUJSfS2T6NnlUDHLKOH4iePn8nrrz2Jz7/zDTxn9tsslDxTQ7JMWcxgFTuWSCY9Bsup7/FRc7FZsW/g3aMQYSx9y5SBYC6f0zIT3ZhQJQRbHbjt8JTTsePoZM7kLOupqXSz5TqU0v1q6FDkNlw3cWm+5mToOFrOmHcywlWAbI2O6LJ+5EBMkOix9siX6w6/eni33GPa2ZIQxqHSL4VN5lL+XUq1CiGQCJsZTHHEZZFGtlmb89lxqVxmCbdYZkQBlZmRkg01w0slS1JkYod8rIWyMJeok8kRbXE2bP0/yi9xNJIR2k0flCSjBEU4vZaoCiI4yOypAhobmDeO3jp647nan7FvBw7NmrkZuWTOABiS8KmuchlaejCWdWhq+bioYLhosCrQWU/Ks35FRP4BFQVh7ZYvpvJMc1ToScg3YmKT4edWiwo5A97qrZaQP0WhtJQeLaTMYlXQ5SpKUJXsJmNm+/yXqkO+DmlbDOJhRqc7+/Cw0G8C3iFjFvRWFgmbDMfaiG9jJUvQJsrMfQ7OS2ZWMih9v56epsjfbTJTyE4g85ErlQhB4ycZtbPdluqMiblcqWp1ypgoTHY693ODBiyrrLXa6Q2YanuWtRBbaJUEAZwrVUDNgEsVC3K/lUSDwZIpKJNQM05Jcxp7GhVYqIk7upvcd7DH7c1NLmkJ9kNSTIJOPZdhVwQwG6lCoyJWBYLOs8U60BjNHEeT1ZQasxETqBKgSUBuTeuxud9dQE+wqTTAZhkNUWH0pnoRQl6Ptt6znArhRcJnMKXNVQoBRok8Z+FxeF/2mHa2ysuX9c4IK1GZh81AJZVnLKsjbiJJZ/RN4SgeNXal8AeiyNFeF6pBt78FpsnjQgL4EcJ8ALuSS+c6tXHsNhFm0vdN24QN2dnqMYvNK8BGTBOFpjGoXF4GPWlUABUMsUnEC05KSshNsF62xMlIVp7HYzbjNoGm8xzOBi71K560uMHFZsWhWXPFnrDQE/t6XW/8ITVc8wesYsuxn7MODevYcjTNWPmWe1Z7GJX4Q1feAcCNaUFvPO3sjLuXB5x4ixttDQzQ8r3OYdEyOEqZhBoVzVIBhtToitgu19MMIn3HbCPEkFLOlr0EEroLxNFgji1o4U1WmXs5dRHVBThppAydGcDUoNGTwowKP0vEeYTM4sWplZnsnT1ubH7nKXrWM42W6aSrwbLtfXWAjQns9SMhCsFECWz35yOLWZFXk4C3qNgYlZg1XgBQURMidZa2AHXKHW91ZH9P9r+aGoZ1SzpqcU2gt772JhedEGisxhZrAgf9CPOhCoqEIIIjADfaRR3n64znsFmzDg03pzlXuzOudqcViVzKymNsKt9xowKHGY0slI6ehVY0ymCUxieHI3AULTfCnDeNt3Nnc5072jM+f/9/84UH/5t9pWmU5ih6RlLtZTcEAppjL/1Zq0WUYN8M9NoRUOzlsSOg6t3OjGNh5XzHpLgxLSpXtSggGQ66gUUzVWH4KY8znow9Y9g820JeoWoPvrcSxMQgiG6nJQt2UXN0tECZxKXDpSDGx0acuQn4fC9cmK2JZuA3H8Y995h2tqhNH0Oy15RJ7Et9knNZrmpl4U05m0xeY6a8wC+QUZIu1e1LvzS1CbcfibNYyS1IKpPjb31O6RlvHV/JmtQoDjTZJIKSQXR0Y3E2VsqbCXLmywY9G5RQPNpY+zybYTxAKeFTNomud8y6iQv9movdij0zspf7J20eOi8C00NqGGLLUZjznukCb1terjew1ZHeOp6wEAThkZvlGUSBT2/LhNVsswR4CdTaMHu3IXQIjSVBtG1zRhnblDml8/ZRvmNskEDjxAroqtsaycmntrQMVBKAYGoSIav4qDbTYGqkLJEDrdQIcCpZ+XwVFEnlykPJhnf2uLEQ5B7XJmZQZAYy5gxXIQt7c78staCBFVRe8jK3XsrGBenqM9q9AGlKtuSClK5rZpZxFE3rGXuLMan2jmuBpqBnozBNpZzZhaRFhSzJ+ufy373V2Px8Niqyb0c6LWXd0qMtLaMT39fy88KKs7setp+HNZqBRmnGFJlSIqZGhA7sMZfNGZ0S1HKDQiuFS5F3h05EEcIBAPt6TUiqOvsy01zPLUmcrQ6MsaExkZlxdNrRaU/I606jw0bCL1eqtE74HPQUq3OzUVeAmWSlVEm943VPCHojDpOBcjEpkXBViTGTXJR7YvBWMmnz/o0LPqadbVJUUn/lFMko0T8ll5a3HZ+GtncSCRojZPmTxgxgV+AOFKFJhL1MoVZGUJKgilk4bFbO8U56hWGuNkxFGcijCho6Z86lx2uXQrAxXcnon9yHTEa2r2IJgZpRqy4IyGcwQMT0UUQAvNk4+SDZZNN72lYy2oNu4AmzYy40ay42S/a1ONsKmMiP8JQMp7Hn3umAt55d4Tev3yIgCxN50sFNLrYrbt87xiXDrx09EYBb+1PGTIBRUJfaBGgR2smowGnsieYJvziwutpy/WMVTmlSJgyJFtI8oHtfSULSJP3TaMAsNc2pYjAJtp1trh4kp3OwkoOXLqIb4asuwZczCUUe6dGQukDqpWebVhY9aEhaZoLtluPf2ePC/GTpAWsjoQ0oHTMxRDy3iG6jgG1W7ymzuKdDxzg0uIWhy1q4ZZIvZIBUyCXKkqUu1x1usvSzCWtipVqcNb72ba0NovqjN9zNMYmjTblnW0gVYlQbbl4lLabJmKqKA6LYs7AjvRaZwDG2hKQ58T1jtFwfF/jMh37QSJa5ii03/SI75mOcWdKrwJR01bztledp7b0slGeRs9lGGYbkGVLkN8Y7uOb3uXc6YG4mPqq/G5esUDxqXx1jQfM2KtBZ+exjPaNRgYtWGqImy/w5TNW3Ld+50FmWkattfVmpMChak0lGcpVNq8B6ajhbtRgrEqYJmae1Rta1pgmkBJOz0k7UkRCkCtHPPTPrJLC530jpQ9lj29n22wsxAoTKfVRBmSHZlpNMKGaQjDIJFWReM8wTo2UjGmAkk9QroXSMM+n16swoFUOZyZWLlkg5K1VCcm+TAJwyGUUBDPlCyFAy2a3ku6CW46SFHKLJxBblpmmjkDuUrNYpVB/QjcjlaZ24uL+it57DVjQ5i4D8TRasdFejyTJUXiSwbvg93jMe0urAR12+xmEzcKFZcbU9zXSPayIaLsA6NJyFjmPXc89qj5REg1OpBu8TQcu8YBwNoU/c85ye0ELoRSuYpSWZJFUElSp7F3rDJIWXeVq3J9e0aORuc1rTSIM2LBCSDxszz3UkBkOK1JaBGmSB0ltOO9lI7KhaxfpU9HR39vgxbQPLpSBnt9HAMSqmZOhbhc5I2LKIu2CYvKW1XpwjYOxGaaZksIWMYrnu6hTC6EUUpWs9TbMRMViOrTARdZNkuE1gHC2rZcfB/pp5N+Gzs4bcRpqaWj5WCtreM64aktM4bwhW1xnVG9OcJpP8H6WZfGbW0q1zpTrQ6lB7t9emffbtwCUr3MhDajiKXUYVp/oD4tgmNKcpIg+eF1pUFLfYE+FLVp6A4ijMq7BBWUc6Leej9JTnmfaxzAH32nGf2+PatM+Y+dqvDXu4IKVjm3vQQ2g4GmYSEOVyfbluBa0dkqrgtSJC0XZeCmCZj1prQZzHpHCTONmiAW6tTIKYnDFXucXHg8Se2spGksqgGa9QNm2AUXmmEpsqH6pWIrWGEtH42CuSzexGGghgxpx1ain1ah0lsqyjKPmDS4/Si2oQHcQZNdst/dewF8QpFwBXyZwpEP8oPcu1ImhVlXOUTugmSKmWPFoTlCCO52Ml0b51flYJu0Gk8dZZOUN4TONGpSSTXxgVuenmXB8XXGhXPG3vXu5ob3KbPaJXTujXMsPMXI/c8Hv8xup2pmg5XffMu4n9bhQKOZVQyoBKxNiQusTZR09S7p0EhGZWmrCIpCZUAJnJ/MnBakEJJ0EUh4wqrqIMZPBUAlUy1DLDbAq8H2IQx61sJKkye5QwpQSf5P5IRPl/AruycLoDSD2ezNrEsLQyrz3z6NySEsYgKT0WgE/ps4YgEpaxVXVsW+fM023Nf5YMyY2WMk7ovWFkQ6+6zlJ94yhl4+IQWhsYVi3xtGGaTcw76n6B6hhiVMRgaFphmxqXLThdyTNAuJVPwgyrA330QhDhG05dx+htzdCvzk5pVMQlcdJH00ycWBOzaIEoHjUEDvRAUJE294wE/CRBSkDhkq6O+IJe0StRFlvFjnvcYT3/69ByMvXs25GZsfR6o01rUmbn0hu2qXetDqUknDTXl/OqvNPoQG88a99wvO7reuhyD3beTRWJLI7RoLWs50ZH2sYzOUvI7aa4VdYOUybC0Al0EBBdBkeV/bktp/4+77nfy436oWKmCWitMCYSMkm/slGoFYuGqs7gGafwo5E6/Haf1KTaJyWpuuD7ubxPOXHWfrQyPlLmRFMuNZN7iDrhDqLQAWbUM1ER2yjaqQpxPMtcAs6fm6IiBgBDaiP+YAPKYtJVjg/EkQDQJPrecdCPzBonN5x1tZxybdjjbdcviVZnHuwWardQe0q9cXzMwd0c2IFnXfhdLtkld7bXuaBXWa0jjwKl5lyZ52p7ik+G0W/GG2Az0K91Qi18DRSS0qQUSVZJEFIQ2KNGJSXVd51pGZN8X+U02kmwk0xCT9IPD4vspCddSS1IItmXkpYSfMmQSxm/E9rGmEe6KpALUEZKz+5irKNGO3t8mNaR2aV1HreRNcTakBmbpPQ4IeXaEqRbE2nnY73nOxtQGQw1eCvcxonKfSzTARqcYlwoUieCB9FIOblU2lIS8vuSBUevUTlzLbJugASySeEzYUtKebzIRJJXMtIYBXNx91LUV0LUWCNTCcUxzaxjZl2dmz+ZZsJtbAI+as5cx8w4XLQMsWGpOkISLuRTPavgymXseLe7wL4euMWeVnH6bQdb9HCH2HCf28uVNXHye82I1Rtu4pg0Z6EnIFJ8msRZELTzpW7FmZOM/HA2iJpSMAze8p7hQH53BlqyszU4Z6uUnguG9dSwumcBfeSO228wesswGawNtDmbBTILFcwPhkqhWdikoFxfi6uzu48D1R9tIgqJVEop0ZgogIG84AIblIEXoHvaunlVLiWmrLpTxn5SI1mVnpBFvOxzi5ShWnamMQuWK5M2hBel1Ax17CX/k6K7WqrdtcQcpBecUsrlZgFipXzRaaSvNGvkobEq1B7GGCxnU8f6tEfZyNA0tK1A4YvgfAJcJu2em5Fb7CmXzBm32WN6FWiIjMkwoOVhyawxRkXp/5iRRTPiM4Q/5IWhXpdm0zNXOpEsbCSOtgKVKFq4GOp1yFNCaK+IJFAis0cuVNTKgKZWG8iOtM7rFrAabFDiKS98BZmenb5WidBGKf3v7HFli36qSj5aC5I46USMuT+aUs1qFQKq2WYOKpq2IavzCH/uBsgEZEa4HOjFDalCUfeRsR6qk49b965sv1lrCv3jtpUxFGBrXFFKzeU4GiNgIqxo4Za1oij+rHzhPJ4qknkdBDw1pKYKxwsHsq1MUKex513jRQ6tqBz1ahJUsVaYlFjGbgPGSo0oEulNCb30wEH6tppUwWYmJw5DFlPotGfQlilKfzxozco1DM6yHhp5vvMP+XuHoLYqArJGmZUmaPnsMZ/jxkrp2PnzZBh9Kz3ZcczyivkslVGrct59eBxktn7KJ0dHbOfrCa+90XLzdZlPd3vRJZdvjfRL/WA2hAw5y01aiDMAmLT0TrtYOZArL3cCnFzI2Atgp87qJiSzzbO9YT9sDXsp1NJKidskyaK9ZHMYhIJSJ+Jkqq8ybazzZCW71FiOp1lFyo3O0i0m3GSZzlqai4G9bmJmHZ31XO6W7NuBp3bX2DdrKfdoR0tkSIZVarg37HMaZ/zOeAWXDJfskoDiLPS8ZzjkHScXhZzdBI6P58TTBjUPtbdMzHzSJmH6QDizmDOhtaSINBQ0d2BDs9kH0qQxa4W/HEl7gWTNudlo3ck5rHKKo5ExHhtRa4Oa1EbpKfe+w8rW+0Fl8pNoEqlRqLVcu509fmxcN8wPNq6rZIjWRGKCk9M5MWwQqU0rPVoVUu3LyqxmYsz9PuekaqK2W0BzjzYhM8ltwDbF3KpB2YieO6bREs8awSQcONp2A85KZKakuFGjKST5g7PsXV7BZSlTFw7nIijfmMDMurqve1d7rKaG/X6k0ZExo5uPs5JPSlIdA7jUrjiw6zqTe46NKmmhXVQyKnUcFtznTf3bKrbV2Y3RiiB8gFPXc23c42TsZaa3TYzR49QGGW11qHP+ZVjq5jjndOwYnCVGvQm2H8RKmb0EK9YI3eJwy4RtYmUIs3bTXjtb9gSvKyuX0YkYEzFotBZe6jKzW1Sibhzt4U8enht9TDvbUkoBcZwhFtKJvNBukf0rchZVRl9zj2+7PHDO1NaOpe0nmZBJxBRJhVstKZh0LSkT2Sj6JDZoZcWGQH8rMVYRUpDj2zhoJZlgpnqsN1TOcq0N+KBZ01Ry88FbQlSMTqIwAU5FgpbeRmelfNRbx2Gz5tCuWeix9mZBmF6Epq3hbn+B4zDjpp8LMbgZcdFy080ZgnxWiBoHpCDfvzA7VRR2Lq/fP/KWA6Sye9VMVGeVJZ1HdwzoJhDtFmFJDpBK+bieM69I0aCCoL6VV3n8h81nq82/VZRqRUKy6IIm39njw6T8J2VWX3RoG7LMHrXFAxC1qs+ggixgofLttMEC+NFCUhL4UwL5iLUbYvxQyFWK5QpQSvJ5yitSS8YYiATfg6xOmTxj83vfeGxGTgsRQ6zqQGUGuNBRhqgrQlpBngeW0mgBawFM0VS92YCuuI+igV2E6gsRThknKuLy287W309oYMriDJWWEU1I0suNSdEhEqAnU18F5CsXcdD1esh50w+gxSwl+WJFX1g3EWOD9FpziVjkUrOQSlS5qlHEFuRaxxxYTV5nxHKg0alet4djj21n6+XmjVERvCEcNzTHBncxoBeO6IU+sLtmUBH8QhO6RNwPFJHxFCFmuT3Slj8ohPVrJWepySQLgMk9VH/aoNeGxe9qQg+rpzjUoGnvsYQ+EfuUNXUV/ooTFZv7JB0OcyFsiDMBRqlREWdRMty1ZHIxi9zfn+VIq8TJyYy4suj5/dSEgoI20u9NLOYji4unXJ2fcrlbMTMCuRey8YmQwQ8uiJNdxo6bfsGxn/Fby1s4mXquzk6ZGcexF+HpX7t+B1ZHbts/5WzqGLzFdh6XQJ1aVFDEhYhCqCkLD2RRhrDF7KTyOUxrkefrrmvCPOFujdBHxqu5953k+yQLVQlIRxEZKEGIAnvT0pwqxiuRsBfRK43xGuXlfaEVCsfUpPoevZbxHz0V9aedPV7Mtp7RdaxOepq7W9ZXLPaWUBmCZrOJ0GrGdUMMgkxFJUaojHW2l+xz3on2rf+tfUig75pomkBrhUd5HJoavNe2RxSHUJ6DaWikFdLlCo2OjEPLkKDrnfChZ/BTyCXMotQlxPjSIipk+otGMtm1a5i0jPWM3jJ4y6KduDRbMQZbifeXvmX57n3YdzztqdfYb0YWZqLTrvYwXcqEP8lw6nq0SszMxBgtq9DSaRF/16nI3BlcEr5jTaLV0t8+czNaE7g0W9XXTn2fBU96qVb6xMq3HI+9iMSryKKZBDWd5nUOOQRN8BptI/vzsQLWJBjJ5zypTQnYa1xUnKx6nDP4oSHOJ5EwnI+kmaKxomiWoqC740mD21PYg8DxWY877VCXV/TNmguHS7ydeOfDuec+YHfvo2EKEThPheRfbZiEKoWfsA5lxrBMIZjfnBBGqXOZZq7xayk3aq8ycYJkQjEldJupwFR22FZmR2V0SD5HRUWmBq2oWRQbwvvymXnUqGa8efwo5e9ROJul3Cq9nxCLtq4SJimFlKlLTzn3grrGs9eOzK3L4swb6rYhNhWKv4otqyiiBSL4rOtcYZPFDdahqVq4RImKQ1K4zFyjcuk7kWpfVeV+bDnWml0WwpB60rd+j1vlXzLgyeX35/IxOQqtcopKnGjoc699izoTreq+tu+bUvwA0B7itMtsH09mMj5CZS5zdKrEBUWrVqnEpBuIieilDFY5ze9H7QhkkpvN7Vb6h7q0Vii3r2ARFKmKoSglz09RV4lh0zoqeIgC5opB57ngzT3rgsFBnr/Nh5gz27KVLuQZ+ac421r8MYLaL/SJ9XslxTJ0uGgqk5P0NWOdbChczKXnKutHgAg+76tRkSk/dEIJGZmiuKCC/C6f56M5h/Itsnwgwg9yPkTCU6kNCYlKkpkYE4kZ4V2WHaUyOFalek5lfHLTQy7frVyvctFKxqzLeGg+53rrb+/LHtPOVpkkpRu1WVxDizjRycjIT4TpUqjEBrW07EAlcdQ0pcea5daS9GqVEzKKECDlsRYUhIVCNyHPciZWt6tKRJGaiLuYMKeG5lTh9mXutgAZ4qE7P/pjkowdZQpJFIKgLY4kKbQNxCmLog+WQSPv7QIMUjotDEgqI533ZwOH3cCVfsnCjlglPZCYpfeMSrxzvMiJ63n7ySXWzjJMDQdzed8d82OePL9R0cvvGQ5Z+YbeelwwHI89q6lhmuxGIWUh5TNtotApDkrUAr0mTRrlMrGF3Sr3mERqwe3n7HVbuSfzUNvjXJm4XdDDweuNIETeNl6Z5Do6DUGT2lzi6eSBV6PeOHCdUKWFG8GuNJw+svfqzj60rG883kQW+wNpb8R7zTQ2pNaLnFrj6VTCOSs85MsGbCZPaaUHa3LfrgBk9O3rukg7J2M91kZmnROSi6jxebwoUsrS4ih0diBKJaZVS1hZ9MJhmkDwRoh0SqsjKZTJ65VOxBRYZzGQpvUYE1m0gmXZazYcy3vtSG8cU7T4LNPntoBdi6tL5pkacsxOMKKwKvDbp5cZfMPTDq8xMxMLK/rZtzYnIsmnR47DQgQPcvl5z4xSgkf4oxd2JKJYGlknYlIcjTNC0hugZy5/r7ygs3vra594DJKZ99bTW1jlltnU5DbYKGDQrvHMWkffeGKSnvYs8yXPF4IwnsaGpvUs9oZ6foqEYjk2EF5q+oDJQda8n2pbYDW2MgbkHwdo5LQyIHPastgrNlmRzqAj1CbLyQt0kcuTneQMSSdZlEMF/4JJhJlErKmNVIF3p4hTBjIUdG1UMG6EppNJxHYjIpC83jq+tBVubTUTC0gog7SU37xfFVBRUISl3WSHSj6r8BGnFmy76d34pFn6jrVquHe9z+Ab5s0kTFEqMIQGHzVtXmD225G9Ztww4uRMWIbghYi7AERMBhjEoIlacU7z0CRCLzSIKc+rJRs3x5m2rgFs5PhSrkhkZqykpBwP+ZomJJsvWbxGiC0yxV7pFaf8OaoNGYVcMt20UXnKFi0bsNvOHhcWcm+uUCUWNDBkbdgi0q4jxijizG+0qXWZejCEoGjbIBiJnMEWbdUylghUNLNLhhQzOlgJiQVwrgcp862CD9E6USZLSi+4gLBMJmZoTMTZzTMfo658wHvtmHu2os7jo2HpWgZvUQg6uQB/QLK7m+Oc/WagyxzRWiXmdroftWKsJDkAEamQHYcZY5QAfE+NGEXNkmNSuZwcmDJBhWSRufytFa0ZN98DVbPMtW+IGZ9SWLW2TSnJOsv2oxMZxNbKtSlJg6rnSNXe9va+tgUOhkzTaLuANpFhysegoxCNBM00NMTl46Bn2x4ZwmU2JViVFXdMQjVb5P7FsuKPWWsp/+qtEmcuAWtX/F8ideBmeZynkyFvYyLu7rmgZS/IdioUZytI4mQh2YRvk7BBmSRoZhCkckZLV4wVbBxHyMFAFM7m2Cb0YSLaSGo0atCYtSHMopRMc1lEd5L1db2TxSOK9uPgG6Y8cP+2ey/jBku/N8lsmfW15HRptuKug/tqeaeog/goD+gULBFFZzbzaI0Ngt6MCjepGv0FL/PMcT/I9xk0qY+oWZAFSwnT1zmOZ02t6+pR0MhhlkhdIh54QWyaJAjRwdTMP3VRROSTlNnIVI5q7tE2YfLsZJhy5cCmrcqCfF6YJdI5LtidfbibC4YUCrJ3M8deUMlNARgZoRjtOrcZHzEyerdedYSVJS0cxoa84Ev7BqiKMrApUcbQEZym6YU56XC+JkTNcmwrK1TbOVS/WR+8E2dyuDdsaezK31or8pmqS3hrshyfZjW2pNZxdX5Kb0Sv+tjNuDnMubmasR5bbjk4Y2ZdzehaLb3be0/3iHuKy91KEMhEbunPsnMUp92ZMbPSCWfxaZhxwy+4bxQUs1aJq+1pVvXZzNJqJXzHUzQMwUrQbz2nU8cY4EK7rqApEJpGF2WuvzGiNqYRHWvYZKAqA0eLPN4wNrh1A/sDfRurWhDkcrzXxEZlQJyczCKbZ6wkUetVh1KJg/0Vk7ecLXu63tE1jslZvDeo+1rs8eOgjOxnqWaVBRGWMkuTNLhz9tNGygxmUhBDyk4xQRcwbRRiBCAI+l3IKcrif2Zo390w3OYxF4c8uqJQU0ktt3h6Sz8wKhlpaRBHkoEQBWSVgt70ZfNxF+RyQTaHRZTMsDgm6seRmlQpG5VK2CZUVhQXDGfLnlXfMswsJ6uecWjF4UQBlRmjOOhHWi39m4NGqM/GaPFZ8zKiqq7k0ThDqcR+O9bZwsLXWlSXlBIHVobtk42SsubqgraR6ER3t84rl2uEfG+1lnMQuwxm0tSMorJD5cAkdREihJONRieZK1lAKPn6KZmlrRzWOgnVZ3n4Rh7jT8LO3l9bnfTs3SqO1gchNlDzDZPTlDPDkpFqlfBJ4b2u/VXbeJgLbiQ4TTsTda4xo5sLQGoaLV0vWqmFcrUEu02eNY2tw3nDRH6mvK4Zs83OG6gZsVWbe7tkfNp6YieZ26wVWbqVF3TvzLjqbA76kXnruNCvabU/d14WduIJBycctIPwF2esh1GJqBJL36GViNQHNI0KgkDOpemFHXNmq+uoUMkW52ZiGTresz6o2XKZ+/UZB+JzE9tkBHWrpbe8drYS84zByrZBcmaTUd8lOXCjyBSquYw/usmyaCUJsSYQG0VohRGqiNMDdW66ON9SrWhtkCpI7uMbXT5P4+aRFB4HdI1xFtGYDYFEcUImCb1hKUc2UcZRghZ0bJNLsm3EdgHbBOnLoEV6LSEOGiAomjPF/tsSfm7gYu4zmoQec98l5dcyQOJcKTQplI7iBNiKdssxlz5MLm8qr0QdSEOaSyaYpi35t1J6NgnTBtrOVYF4kAdtnCz+pCVMQuu2vj7DnBpYRGiEPzjGyOV+ydxO7NkJm0tCy9ixDC1TMEzRcjL2Vby5tYHDVnocMUkkWMYIosvsXFvXRzexzgKSb9AQzSbLhwpikyAjk1k0SZxtZvhSObuo40RJyst65olLiz3ZnB9/xWF6L+jsINybSgvbVHSZWayJtfJBVCSrpV+8s8ePnVjME6SfWQTJC9sQkHWaVc2UlEoQtTw7GSDTtR5rI8ubM3Ca1Hsg4ZzJFIwe5wxu2eRF20uAHdQ53VUQpzlkkJD3JgOkRBmnbc9T3ZvsoItzCUnUiYS+MKOp81zt0rX5O26euQvdmt5KtqtJlaZxioa9ZuTW2YnwKW9p4pZS8MpLYFuc9w0WrEPDqe85bNYc2IEjN6ecSb3VWprriZAU19dzDruBg35gZgS8ufINk7LnWJxkTthXxqaUpP219qrSJMaoJVDK5eXRWaaxoZ9NzDrPzRt7whl9QdeSe0qBkHvbhSEMYNbIiGThudZGxrY6E/DG1DHRQg2rdEIvHIHNffPe7LG9xNgNLWIFy2xn9F1eUIOuWQ5O0d5nhFpxJlFdnZWKamsWNvcBm8R0WXOCxu8FjDeSGTWJ9kRGS5KF0Erv75zD6KOoywy6OuiqLpMdh5rUJoNzCj3m8mkj4gOCYk6576iqOILKSiXF0bpgMmuKZlq12CODPwTfa8yeJ84Cs/lE13j2+5GZdVxsN8Pq69Byn29559kFbizntbRWpLwuLVZYHVn6lpUTmTDvTZb3ovZMQUpeCc6XiX2eQxyFdAJTeqhkRHcu6cImUMmo8eh11SamCJykPFNtEv4wlBchQVhbWfyAUKguvcwBC2mIOnecoh38gbghd/aYsQuyQBodMQgVY5Ofo4roVamS/hfKvq6fah8WZPFtFhMpL/ogbZQUE6PJzEOt4BpWQ0fTeeg8826SRTyzT52s+3OHl0rVKK9bCREzMEq0deNWiXp7ttTl3m/pUUqG3nJdz2lN4Nb5CUNomIKpvdyjac7aN9x7usdeP/L0C/eyjB1T3MvcxaIW1OggpWUVObDDBoVceJKj5VpomBnHTEkgM8aGG9NCHHsn73vC4oSl6/jd04tcnZ9y2AxMUUj9V5TgYFMmXrmG9apj6Cbmja5UjdMk7qsw5C0yoUdZs1JSzPaEu71IJRbJvWmymRRDVUBVCayWUys9X2eJUWZyYzqPei5m24D256sDD2WPbWer2YCewpajBHGWNovFh1zuNQnlFXYNYaZqUllKO5XFqFgGJsW5Z9TCUhQLMYZJ6BHMBL4HrQUfVH5ASsN6zONDRsBOsYgdJKpTqSCoADpAMKUXm49BJwkW8rxKalJlpJHIM8+bBS0P+qQxE4Q8MtN2DmtFdHrRTBx2a/otQeYpCj3b0TTjaN2zOu0EEp8DjqYJLDKq8WTszzn2mNln6hxNsZK5p3xO08bZnbtWJVMv5X+dSGNm8yrBT0Zui5j8VlBVEN2daPkqlYT7OH8OatOHq7zWxYnfv82ya9k+rqxpPVrpnKlsskWHrAeqLM65j1p6tbNuIyJf6BO7btOjDUFaPklRqzpFhzp4XTEVXQYmFcdRBAmKwy6qZdsjKCkpKICelDmblVSTSqm20EGWOdTiXIbQ0JrAgR0FjZwMMckQ+to3nE0tq1UnZHhJMwRhpSvfs9FyXAs7YojMzYQmk1poRROlBbUODXtGkMpABVfqLO05NxMX2zVL13E6dBx0A72RbNJnfvNyLkuJ3GfMhcuo6SKbV86vQsaBZtZVgYACcpp3rma99TyC0GeiCSGh2lR79DHJOKMPOq8dupaay4hQsTLrHJtHqYz8mte8hh/90R/lTW96E7PZjE/6pE/iW77lW/joj/7ous3zn/98/vt//+/n3veX//Jf5ru/+7vfvw8rXMYRCKDuNzMLSBl3yLOoC0/qIuMFIbdIUxZeVkk4cyMZqazq5E0oziD3/NIo4ByVFO0xaJ9Y3wrRiiMH+TfIvmIvvY4qrF6yvTyvFeehoqdVmU1ViEOftAjcLzWqSVJWtsKCEr1iWraVsWlatvIZ2VGPt3rsvuPyhTN66+mMZ26lDLNvpe966kTP8sY4556zPW7e3GO2GLl6ywmzxtEZT59h+kMQVphQ+i/dxFmUcYMi7LDNTZpS0eGV0j42otoo59XqzfmAc0GFbQNuMNillupAk9l1PKQuL0KzCF5hjq2Um2dhA6Aql70474T0iMdMHWbFeaellblsIOxFYvPwotOdPTL2QV03gOm4Y/6E5QMEzJvsBA/acYueD4zeZJKd9Rx0AyvXVtRviJqTZY9ScOstx3XhnrzI8km/MNYxoXkmaDieepHG3BuqiIHuErH1dda3BAQg7RuX5fqUSjRaKBlDUozBnMvOjI5cmS/pjeOwGbLermLwTaVKtFqyeaMST7p6A6siZ67jPcsDrh/twVW42K5wUb6nVQGztcaOSVjl7h33M7hycy5XscUlUwFaOs/hrkPDohl5woH0au8bFsI1rc4zQIGgpWet42wmALWzqWPKNLUX9tdCRtG4OlPcmsC8daynBu8Nfesy05MEJr2VLLjPdJblfI3B4KeWmODCXLieT3tJMKyO2FZEXaZCh9s4Zi2crTvcdlvsvdgH3Nn+9//+3/nyL/9ynvOc5+C95+/+3b/Ln/gTf4Lf+I3fYLFY1O2+7Mu+jG/4hm+ov8/n8/f/w7yGgo253/dV9T/Iwq42fyhD7BRHW+ueakO7uCWlVxZuCg1j3qeKqc7kJp3yuEqqNIF6UsRZqixQahsanfIxbYklJEWd193QNiLZoJAdoazQjUVvZWDcyYNX+6BRnK2ee/rZxDyLFbTa53GfTTllHRpWvuVk7BmmRjLig8iFfs1eI+CphZ3wSfOe1YFQl6UNgq9k11X5J+Rou9Iw5u+YAwCVx7GkyV5quDnDzV9b3V88ggyAI0mZv4zvqByYWKiUdybVc3aOOKNcVyUVCbVNz6gT9EIYt7NHzz6o60a2Rsdz4vAxlxtjUlkVR3p4CVn0i+BAZz29cZV6UCQ7I2d5LOigLRWjTYZVUMMDMj/a6kBrfEUpz5pNVmb0Bt8BVIdQqRKdqkAdm79DzFSL5fhjAptBSL2RwDnkrNBngoiC+C3jT4ftOh+3yP/FLfk4n3QOtG1dayMieScjRZpWh3M92nJOty0mxZQdd6uDUL8mXTPncr58Ho/SyHcqs62F+EIrmDdS+i39aciOURcpPDZVizLKpRIN0FtfP6tI5RWb2Q1rVqGIVCrV0nwZKWp0ZDU2tdj2vuwD7mx/8id/8tzv3/d938fVq1f5lV/5FZ73vOfV1+fzObfddtvv67OaY0M4kPnXBMJR7HTut0ZBx+ot4FJhWYJaziwpbJwJYlnk3KSUm9qE3nOSCXm90WbNYJ7xYs7idASTNWsBFDQ3De2RYriSRBpOy3aqFc5TRpM/OJfBvSLOI3GOZOlJkxYe1YLPWbBuA8YG2lYk7IJOpONWvlfuBeulIe4FLl86Y944Fs1UwQ1nrqvMUD5qzqaO5dhycjKjmzme8uRrXO6XXO6WNLmfAwKuuNCtWfk2czBvwCNdPwmTS1T4ZSdObO7F0WUUuNDP5R64ES3ZeucVMNlgSI0idR6ahF/kjLWNG0WmElBk5xxmGbwyiM5wmNK5IKmWtvM1LuhzJotdSW882qz85Hd15EfTPpjrBsCtT7zJpV6cYkz6nJMAmOcF/MpsCUCbS51TtNgsR9eEQDSKi92KVgeuzM7ytjJmMgSZy/Strgt7cQxSZQpc7FaVMakcg0+mgnSA6iSKhOaUy6TFYZe51eLcYtLMGxmr6Y183onb9IS1SnRWKl2t9vQLGefz2WnGpLg0W3HQD1zu5fu/Z3XAyrXVuf2Bg7urVN7CjtzWU503SPm4144QNTfGBb1x3OwWHPk5Z66rwuuXZiv27IrObCpLIZ+78r0745l1E7PG01lP168ry5XNwvdy3jYOetYIgMsqcbR7zfgAwopyLsp4Y9HTnVvJaHvjcnnb1M9a2Ik4V3VNbUxgrTy//TDuuUdc6uT4+BiAS5cunXv9ta99LVeuXOEZz3gGr3jFK1itVg+5j3EcOTk5OfcD1AymLOQFbFN7hLkXq4oT3iYzyJmXGRV2lbOklCdVslIMbMZOan8xi5YnDbGTn2plmy3TAfR2mUFt5ue2HW1xEulBMrtSVi7CCbVHWjO3zXaplRnjMqzu87ztyrecTR2nU8fJ2LNyLaFkqTbSt47DdmC/2fRbYpIbzWUYv0D5z/c/IM+tbZFxpzyiU+QGQcBSMVcGlJI+VqW+S2oje1gehJzBSp+29Kvz1yyBUqHfLJnxe2udFMTz1jUqHyVKhg8zPN3ZB8U+EOsGPPTa0ZrzlYyYM7RiJfvTOegsC/9m+/MLttVBxlhqZrn5+3aWVJnkUOcoCIujLc7i/p9Xtnmwv5Xjq8e2dS/7TB4xBJGnm6KpIgDiWLe+c3Ys5ThLtlkoFUHK5S6aKjxQ5nDrseXjk9mOVMFTPhquT3ucOGGYquM2KgiBTnnv/Wgip2jqOND2+d7erpTHzwUoyPFv99fvv+/7W8mK35tpJWRA9w/OHo49ogCpGCN/82/+TT75kz+ZZzzjGfX1P/fn/hxPfvKTuf322/n1X/91/r//7//jzW9+Mz/6oz/6oPt5zWtew6te9aoH7r9NmHYzkC7sRGozXhMVOEV/nyZphNx+yzEBtDcV3VHi1Gr8fhQJvAR6kDlYBZJVqiBzo1HUg1JQTKkAonKZs5KiCuuUOwA9CUmDS4jebauqugdBoWVaAJKSquu2A8mqNJSZ3dx/dGwxznQizF4Cj+7yOkeBjtFbTseusuWshlYYUWzA2siVvSUH7ciTDo+Y24n9ZqgzZsvQCj1akJm53jqsDuy1o7yOoCOdM/jJSuZvIxiRDUwmYQ6njWD7pNGDJu4F9MxjGiEBmHIPnKz2E3IFgS3nXfrptHL+zbEh2UQ4CPV8V1KM0vMuP/k+0B4BqSW5nrFN5/SDk3/E486dPUz7QK0b8NBrx9o3LF0GEfHAcmdxNKWEGJOXoNW1QuyCYgyW0VumICXcwTc18yzsbTK3GRmDZQqmOuQz16FVqvO821lXyBnmNtpYq4TX8lopw2qVmGVHVJjgCt9xiLoGxT5qBt/UOdWjYcZqarA6MlkZ//FJKl1AZVUqnz8Fm8vRnlMn2yx9Bxb2zEhgk/0B57iSS6a48i1vPLqtcqo3WoQFeuOxKjJmhjqQQOfMdVvEPHYjwpC/o6OU2m3+jhJQ3P88lzJ4yYRL9l70c7cZpHzSWBWZlBzLEOyGyYqE0RvQWXn9aN0zDh8CaOQv//Iv5//+3//Lz//8z597/S/9pb9U//3MZz6TJzzhCXzap30ab33rW7nrrrsesJ9XvOIVvPzlL6+/n5yccOedd2a+BCGvSJlHFyB6GfVJec41WnGKeqVrTzVlUJKfAyhCH4XtKfdyzSjpZPC6sh6VcrWy0vtLTsqX5/uDm95sUuT5zcwy5TQpbUrNqCRSfaXkmceDzCqTT5T9lhGYyYi49TZCITNIoZCMtvFZY9Oydg2rsall3hCEE9Hkmb/CldobTyEFD7kMtfINU7R1Tm8IcquElNGTzuKcJQazKc0bqdemRm0cHWyCBw1q0sTYwJ7Qq5W+dcmAY3Gs+QSmpLJTVCgrAg0yJ83mPObzvklVOZ/5q0RshOta32jIYM6NbZecd/ao2wdq3YCHXjtGZ1l7mWudvM2SaZuFd2BDkF8c6SYbzNt4KYUufcsUDTfWWY6ycYzBcLruaa3noB8rD3EJZtdOkL4FugFSPvUVRcw5Z2u0gHuk5CzIXBcM89ax38lxFKRuOb7ymWXfMclURPn7jdUMo/vqlIuD3i7WlaDh5nqBC6YCjE59h9vKODWJE9+x8i2zxcSeKiV6xZkTEYNWBybAeVsz/CFYfNKVfKP2pTNxxZhn+W2mwtzura5cU4OUkDRr11SHXL5P6fGeThLcFA3wcu7ZOv/3f73cDy73j7eXGpXP6emyx50+ynO2X/EVX8GP//iP87rXvY4nPvGJ73XbT/zETwTgt37rtx70oem6jq7rHvB6MoLS80Gj1pLtYKNwFJczkiD0Ce2gu6EIvWK6kB1rkxhvi4xJ6P2Mydy7a0VzrNC9YtyTkR/diuKMUogIAeCyCLkcjPxPJVXh6wWMFS2YtcIE8Hsqg64iFWJYyt8ZiGXPLGaEwegtp5LAieRe0kaE7O2G1L/pZMB+rx/lBh9bluuO6XRD+qtaKd3uz0b2u5E75ke1N7v0Hceu58x1DL6pN/l6amROLaMpO+tZO8vZqiM4Q3Sm3n06CzGHDJCqWsNGsu8UE+ZUxpJGIPUysoNKaJuVVUZTWZ4qJNxKj1e3wvoUFvfLQk3K4LUH3lspZ71pFjHXLfu/A+tbFOPluNn/lrPf2aNrH8h1Ax567RjWDaeDoIXHoaXrJ+adq05uyPO184xIXWfS+cIM5aJQIvqgq0D5jWsHAFy4fMZqaHF3z1nue8KlLFSQHbeKmpunc2JU57VuvcZPZoNtKK0PLQ63n8mxFCL9cNqw3HMsF+1GYSir/GiVA4nJYoy0iYIW8YGUhHHq5o09EWxp5TnsehkR1P2IIs/q5gz+PfdeIK0sl+44Yr9LXB8WaJU4snMOmoFbuxPuGy7znpMDrvZnPKE9ZogNLhmuLfcwOvKUwxucuY7lJGuS1ZHjacboLctR2lpWR4xOdSxq9IbOhko2MXnLhHBbHx/PhbzoojjW5dAKP7KOFbFdxN4rOtzJfK3N7FHOmc17nIDCYk6wDg9W9V4AztFvGpP1hq/N0De3SIfei33AnW1Kia/8yq/kx37sx/hv/+2/8dSnPvV9vufXfu3XAHjCE57w/n1WL2Xj5DXNWc5slcHPo9At5v6nsBFB6Ki9wOKIlS9kEUbmpbbHdO7/ebU3mVHMpQdc91WaitTsOTYpy+5tZ11sZm1L1rdlsUnitDW1R6wyylYlRUqpjj0J8YUMdhuVGFweDl910iNNCpVZsvrZRN94rsyFOarJgIsTN+PMdZy6vkbu88ZhVWS/G8+VlIyO8lDYQj+ZJOOOWTNSpY14fHW2aSPQ0CSyQKFUBZQsJsZ6UJowCXAs5YwX2PTMkXaBPZagI+xtWL5q3ztntPXz86gFOhFmidUTFNEm4Z3u8rVyuool7OzRsQ/mugHgVg0xCWVf0/o6Q1nIWqZJhOBdE2oWlpLCe8UwzIiZ37htfS01NzPJcMr85ZQZ4Nbrlqb1dYEXHt+YaU033z9qQfJrI5ze3ovSTyzTCKXc6TPVK/IMCWOVSMUV6bjWbtinpIXUYW2o6GtAAtwUZQY9pY2EX3bG5XwAHB6u8PuaK/MVnZWyaas9h42wQFkduWN+zEE7cMGuCGzQznvdJsvVKjFvHFMwrN2inteiimTs5nyXqYfSdz0bOqbRsrcYRMe338w8A1WFSQHD1OCdoZ9N5/qwhZCkMt8Fjdai4mRtJMZEMhtaxslrplEClq53OGcIXs63MZG05wnhUSojf/mXfzk/+IM/yH/4D/+B/f197r77bgAODw+ZzWa89a1v5Qd/8Af5rM/6LC5fvsyv//qv87f+1t/iec97Hh/7sR/7fn2W7j1KNeC0ZKIetIPV7Rrf+9qTi11uvnZCjF9RrQnUlFmbrJYsKCv5qHS+spgowB9NROgDK5mGEWeonRIna6V/G4tYuc5cyqXUmVLN3FIGJW9bbJD32DwqY4XUQm1n0VEEqJUFvTU3tpoahnVLOG5rebTpPId7a67Ml+w1IxfbFZ2W7YXMYs7StZyOXR3uP2zXzK0QX8SkuTnNBGyRZMi7sQGbOUPXUUmEnMFfCjn+EiFqnarOe2wTFAH3QkqRiTOUSgRjN/3WAj7ecrbJa9ojRWwVYSHZqTpHcylBSgFsqVECo9RCmgfGg4g+amhOCqsX0ufdOdtH1T6Y6waAXlpA+nomMw/FRJXUC6M4Gd+aLTY1ROnnpKW5aXC3UzNfgMV8rP82JmIXToTnVyIeb00kJtAo2uywSskzJiFNUEZ4zpvGE4MQPVTFMApuQ0QUSgvNO4vWDqUi3ltSoqrdNFpYsMZ1Q2g09Fvo5sbjlRExhbRRwtk2H6UT+9SL16suNojc3cJO3N4f1W0/anE3cz1lTWwBUAEctsNG41YJ7uPe5R7HZzP6ztHajepSIaDQSgL0OncLsq6dWcJskvL5vFDHyjFvO9VptMSlJbSe1vqKcWnyTLJzVjitvcY2oc40F/apMoObMMTBQC/vdZkHvuxrfjDg9OYeeG/2AXe23/Vd3wXIAPq2fe/3fi8veclLaNuWn/7pn+bbv/3bWS6X3HnnnXze530ef+/v/b33+7PiKCUA1QfGS6aCVmXUpjg0hVlqUJmZqbA2NeLE4jwQ+03ZUp1alFe4vUQs2ripZEqqZpQl80oJ2T+5P5sEXBVnUWT5/GZciKgwJ4bYJdSFiXjW0F43+HkSTuZCGWkTwUKaZbH0DPo5p8ebs2mR+0qMTnocq5NejrWJmJnoNx70IwfdwF4jPVqjEj4ZzlzLmeu4tpI5RqMjF/s1F1r5aTMV2zq23BznrFzD6Vp6PDLgbXB5kUg2ivh2zKUslTBdlBGlHG2fmzfOZfCSnackNHcMeuNsA6QkwCtV5LPawHBrzHKF1EClOM7UxUpcQRDlJFCElKMnrUk2MV2IAm5zWWVp52wfVftgrhsgAXglsldFWGPDSlSAl6UV0tiwAcbMPU4nmlZe66wQ2Bf2qU3WJM+p6QMxGJZLI/zcCbrFhvZRqTwLmhW0vDO4yaJNoO0dTov48jA0m2PKGI9C56p1FgvITstHjUqKYZLfu5x1h6DxSdWs2tpAUBLgNo2II/RWxomM3gjJz62j076yzrXa0mlPSJp9M3BoVllyz7OKrfyElnVo8UlYqq65BfPGccvsjDgXrdqjdc/pqmM8kVL/rJsAzeA3o0w+agZnMTaAiAoxesvgpPc7b2VGeRtUZptA3BdnXRjvQCb8Yikf50SkbGO0UN8qlYhRc7yckRL0h2MuG8tap41UASZv6VtHN3uUnG0qd+dD2J133vkAFpjfs3mNUhHdRJlxLX3PbIXyTDu56UPlZ8x/z71AUh5VyfJ7Kvd5YyHMyCXclDPTlLJOrgZins3V4LuI8qpSLuq5J540VT9XJVBj7q3YQKTBLgXAFRdJHE8hZ9Cguzxw720FQKWwoTSTfo44Npd5itNa2LJUH+j6iVv3z1jYiT4TWzRqMxy+8i2nrmc5tkLE3ngO2oGr/SlzPW3ACrFhyH2V1WlHO3Ps9yNBC3er0hGlM7EEoDW1LOO9qALJl5YaekKoNLUVZ1zGmWJU6ElvcSXn815620jG4C84uV5uK9PPFJpFCSmsLPiM9gaSkxsiKYh9hFmApRUgXAKm+8MkdvbBtA/qugFQgkMFJs/FFqpFyAFjLi2npEQtJmq8lgU6NdKaSVCzIAHkUJ12ChplRbXHjZY4GdTaoCL4VgjxS8lZq0TSop0bvGTWdk9k+GKeJoj5fleFyjW3oBQZsVwYr0IJGtRGFKHx+KClNJ0z2LbLKkW5Amazwk1nPK0JtFqcbh3NUalWxLRKVcu2UYFLVmaMTV5cN+NBAiobvaiP6UViZhy0QmpxtO5xk0WtMzAsyszz5Dd90JRyn9lErJVzPnop95fAPibOaRJbG1AZWxOCCBaUWywG6cvqJtA0G3nOxqRKKBKhlo8P99dVeEWphDZFYEXT9gHTPErO9oNpaubp2yDRpNkIqqu1yVSJ0oP1++IE2/sMoYNw0aGaiGmEPpAkN7iUhRHHvH8+q6SRcmaym4ewCNWHeRYZ6LOGbqugFwKK2BpiycIgA34StmTkVzSxS3V0Rfqz+aFS8hCphaiFRGekJ9okUibocOsGlxTmZr6Ui4iaefYP1+z3I/uNlFqmYDgaZxXyDlSd277xHPYDT1wcsW+HXAqyuGRYZtThrfNT9tuR65m7VcAKBuesLFg2yDlMoHP/qJRltpHiJCSgOLMEDWruQSfGdSNI5D5util80MGIk7RZ2qoNhMGiV7likCDOUlV3AqSF0CTcgbQQSlaNSZIpmwRLUAHaI0U62znbx5OpJjIeLZj6wGJfnpGSvRTJzhh0FoSX94QkWWfTembzidNlz7Bs4RA6G5i8uJrak525HHRKbzj2mqm1cp8rqYo1TXEWAg7qemnPuNZWNRs/WlJU9HtTLWl7b3BYtI2oTKg/ZZSvNuK0lJL2jDWReTdx/XiBO+ppDkf2FkOWiQN1UZ7VeTcJ7sMLj3KheNQq8p71IaO3jHPDnp24pT3l0Ky5vblJrx1zNXIj7HEjzJnriaYNvGe6wBRtRXJbI13cMViuDwuO1jPmrWN+yXE66ySgSAJaK9l+1/g6uuiCIQTJSoGKG1mOMtJYwGA2awsrlaT07DVplUULLg6YvIY3jVBBrqcG5zTG5DGqDI7rerl+ISrOVh3uqEfNPf18Ylw3pKBZ9NN5ZsD3Yo9tZ6tFf3Ly8RztIRGUJ3MFI8jjpCVrshvWIKUjxM0sqyoyfYo606nG3NtLBcyz6R+WcmeV7MsI46SVIHMz8xMhbWY6VQYMJSldx77QOeZMjq19Q42kJBhAEMx6i5A/j8qYVc7e9wXZO8+ztlZHpgKvd21FI26LJrdGmFEOm3WNVtexZR0alhmSL+NBiVXTVlq5kLVsi3PdFvkBKqnIuZnZfI0KfWL5PU6mIoOr+lLZNsnvUpbLhOtK6DHrZiqeo2hRShDeqUglZkdb1IOULqCtnP0+PPT+zj5MTKkkwMj7zVerfE9Usv98L27zfuu87qSoSZM4gLA1NqRzlmmtbKuVlB6TiXmUMH9Yfg7L+IpSqfZyVd5P3HqGrA21L5mSwuuUs9pSGcqVrq0ycRErKao3wr2eaHLpG2DWunPbbHqgYSOsnmdefeZHn+uJPTNwyZxhSrUMzZAaeuUwKm4RWogTLSNGUzSi2uMN+71n1uQSd9aojVvnpTEBrYRbQOUAIsUS1IhTDdsZeyX/yRlqlGtclMZKBUCqbxsu5jJmGDIqPCVFkzXCpVpgpD3YyblJQUCVISrM48HZxtFg9SgIO5NEvs3lnmcX0XOP0olwImCh6VIWY/dSAggI4CZ5hVobtAe/L9toG4mDxaw00WeJrbnHdj5LaBVvyMZZZgdanKkb7YZPuaj9ZFDDdNSJM9/qv9T+Y5B/h9EQraLpvChQrPPoj8k9zyaTbAQlovdaNF67fmKvFZrG43HGzWHGamxxTo67oP6ecuUGi2bkYrvGZuDDkZuzDg1vP7nEcmwrR+kTDk5w0XBjORc5q27i+rJF3dsxHXrM3FPYsYokWYx5Dlmlc73mZJKwPymEUCJq9LGVazMPm8Ake++UCTDSyhJUEhpLnQgHHuV1Lc0T80OQ0mb0y+bz6nVlpEq5bZC6iNew1pq0997LmDv78DJtEmrPobd6dKKapWvJNiVxINpGpjxi1/XCx+vDhgXJZ3RqCWAbm6tteaGGDRGCBKBgrATR22IDRkvvONR2TMQqaOeOFNUDGKVI5VkzGbsR6XtxXCmXxderltCJrObefGR1NTHvpwpCEmcu86gT1O/go2bpu6o3+xF719EqcrWVFtOtzTELPdKqwJQMQ2o4DT1noWdU0n8LyH7LUbe5BHzvah+jI1f3z2pPtjj4eTcJ1eXUoIsSU5L54yKDd6p7QtA569UsV905BrtiSm3WVHuLZLRNI9rARkdcMJwsezlvs4lhaIihrU54mgxKGaz9/7P3J7GWLWlaKPj9v5mttfbep3H320WXXSQvm4KHqoqSknyCCQKhN2BCjlIMGQIDUkwYQY4YMkpmCEYIwRjVBGaFSKlEVUlFPVU+mpcE0dwb9/q9fpq991rLzP7/Df7fbO3jEUHe5GVk4uFu0pH72eec3azG/u5rzDdcv15Qi9Gu1BUH1xKB+uXC6BsdbOGtl+17y9wa+Cm41F9Fq3I84AnBtCW4C1/403XD8nbyNLqxgK8nUoutPWqDGxvq+vwD0rLj7b1CzdReG23nkh5D2+MdIOSfSSo/rQ61vWftrWxN1oKOUTrwoiGH5xyxLnFDGjqgwgTVS9clPZbR/GrL0An8bVV/rh91HvRSk9jlLjeqFDbkdtswmuKTUk869PXH2zltlSjC09dKavPzDoGGB3yFLmbU0INtA7b56/X5O5ualNR3wfZtWq270xtEhVFyNNEU3a6P9rvWSm5qUoSl2EgHcUOxtp+ZfOC2V7wOvgJtoxZRMoYfb9ef8T9N25gacIpMAJ8Ivdpqiy7+tpTgVdlGZ1KfIwdvnQZ+KvfYeMLhtdu7S0jC5CgNAGVf4TV+pIA9uD6VfxTlJ1W61IAMNxEgQZH4ZF+5/N3Lt9PeLZMaWrwydo0+7ceiiQ91fq1sjyc3i79cHSfCLQkySpU4tZMBb/cbMCpwxSmPqHPwwsqObf0hgf6HrTc72PKFTm9m0MrghSAHRZis+lGFt4TRZ7C0sreLtVecOlnW1aoqPUeT9Xt/7W2cxh/VanPI9CqAqlF1TLxCvFIjm/VWOyFg7ehYhLq1n2kDWlEU4DiAFoIcKhBdF1gJ5ehIrUmecIR1ZfBYwdHNDoLisF8Qg7hMo2XJp+OEeoxINwumycBN+5TxwfiIyAaF/2Ld4+V8cPm5gBQqnu/PuBltbvOwmonB7d6cQRTAuMuY3yegsrWBfb4drr3V1RDcZG3jcORNV/qqGs3Kucp1ZyjiMFZzD/LjR4WAXTUE4ODH9xyBaGjresF1pqgI7i05fieCV2D+QLowiIq37H3eTdnnc4NC5PevdfpuvbmrniOUInQ0kMx6GoC7ZGOHoKCx2piJvBXMjWcbUHJALYxhytjvFwffbAbzAJy6QijSzMqNnxlTRRoEybEPTWSBWcAwydbzeUB+GBDeF4xpRooVuQSc7s3CL04Z6gGq8YRbR+n82R5QYPraPVLKKIP58C4logo94aW2ELFkCwMxSFfMiiy4cqOCRBWfrwdkZeyDgYE+LTfY82JiMxCwB18BIYsZMNyXHc41mXNSiTjN4+a7vbP30oxNWsBSOAfWO2qbd621mFUJ+fs7hDNj/mYx/1/vCjS+NJNiXqM5ogVFiPY4Ad3iUDyBYlaUwshr3HjGZ4sP8XrpHYN23MpjQvosIr9fEA7u2Vv/iEQt/lBXy0qFQTMbzzKgz2/zEr1S9LalWjtXVbeKtK2LOUr/mWIT0leTS5TVTiCioI7agy3iFgQ3+zZ/TtkCwqXYQxe28BNpc9/2PuBzBPS/7QNKUmANNvccnQSexIIzLNNaSqMJkGXCu4JpytgPGVdpxRhN37XZ7H3veINPPr/BYb/gdjdjF61l0xwwjjSgAk+yUO0V9tNj18AZRN4VeC3za+NpImydhbjNtdW50FQIzehdgS15uuhGdFenPov1BGWvCE1IxDsWGryd3dr5gLWekwDvgu3btZ54MGMb5TjOgpolZEMne7Vqs1DtHs7yWreHSC+4swaqMhpQsJFVEChvVpXq90sDN0V2YR0HTlXHlFjlbK8hvrm390hklXktwXAjcCs64S520d8f0Ln0/VD4vvHE3ABq3rWwdvMuZOwA3IYzrsKMiVYMTvWpauF2kYTHMj4xXmiVPsEoVgjSP0fHfVTuHrVTKn3vaM/RNZqdQ6xJUUk2d1VugMyLWW01fjIPJiwiYiIb7blq3dr6zb+cnS7amlxSjW4SLxguCM5SCertZmz78u+x3uhg24LLskSMnxtftR5kawN/MZgA/XsZFMREFiKAVAwYcUkdid6SXcLGxfWAADZRCb5PCCdC/kpG2q8o4WI2CO9+NiH9qECswDk8NYTv//ebvd3cBNBUTVc4u6rVay3yliwQK2hmhDOhXBHiVMBhQzXWGjCfB2uFkGK3W3HtXNspZFylBYFM0OJ+nfC9+xu8+t4Nrv5DxMP/yPjF97+P67h0D8xVIu5ohwzTRG7zpZKDKS+1QOdVpmQGBTNzt81kU5CCf4z+N9l5tXu7yZpkY3gIaDrWUtjpUHbT6mLHXNU6ArqH2w9uF3/+2oK8BvCjzblxnbfWfzK6WAv0YagI4R1C6m1aYagOprF5LUdF3VejpLmCE5Eir63qM+pPhlWnRMVlE+NWUfk9vZbgfqqm6FRyQF0ZWBn1olfbAkOthHUewcGqsxgF8XoBkXYN8lrJrnUh1CWAh4rROaKqwHoaoAtjeLZYpb4aS2Aa8sZ7ZwAwR7BdzF1o4nrCE3AXYOCoRvMJEHxlvMPIGf+n6TvY84IDraggnGTEEQNOdcRn+Qrfm287Rz8rd8eeyCYZ2V6jCuOc3TdXCafHEVDgetcQ0NuxbAXD8XGCLAHD87krd6kSxtFdyno7XKw7NgdgMCT4ulhoDj5Pl8pPzgEBvdVcB9OSX+cEFsYwbAIkYaqozwhhVxCi2ffh93AKauuNDrYcjIzMrMhX4qL/QDMTRzDrJc0GgoJv2jQ4JzeJtZ8zQSGdN0vqXFcA9RiBqOBUIaN0eccyp+19RD+5ywWi1rNjm6ViMwy4rJxb0FG7gWz+2tIq/HChhZZRTwINBPasq80pTqexfx+itciupgWHtF5knIwihJfzAY/rgPOSwIeMxz8GPH9+xMGr2eyKUYvbc4nSBv4QMrrPxFsi4FWnngI0MOiq+AwMpqg16GaBCDj4aWvV9UVqql9A/93Wyu9jAe8KtMfFwV8cXeotGE2LF5/DtSqltbbbczs6UcO7yvZtWq1j9LpiUluNuhZifXJtBq/MLJDCEjunolxWVsyKMVl7l4MgjIC0PaVsgKCGPyC2YDGfBrDjLtp7KDn0ypaCQrk+kWesDv7DsP1NupCZbAbqvcL0faCZpp9d+zewoaH3vlcsEnEVFuzD6tVs7oE2kTE8KggPdYfv5ueoYFyn2Ti2jlwGNgelZpTQBCR2qWAhT04uNKJPa8L9966BqeLZC/PTJT/2mqhX4qpbxd/UvUQYGqsVVl69ihDqGjqFC9i2X3tyfUJVbIj0xopo3QuRrQtiaPPai5svs97oYBtiRRZGjILlWTGRC0eJNSUmsJpkn1q1KoOJ4hObsIKeA/jMtgcH3Sgpyeas4S6iXleE/QoZAypg1Vhmm+84QAJK4FOwueIkPUPWyTKwEI3TW09x2/DZ2r+6epU92t8pYOCpTB0ABfIquLVgvRKMqfSLQyqhPCQgKtJhxTCY48jVsOAqbVJyZmwd8dnjAfOasM4J1zdn/PI3/zMOYcUuZJxrwiIBq9gMd/UMtDmalJocGm/Zv1SfgRSAzsFm2JMZBzRjAZmeVuoqBHJrvU1P2boCCnkaFGUDRvHk9mctePo8XMGoY7XNyquAOBOqbp39JyMCssAfXBLz3Xp7VuPT9pEO6TbO8Wuj6d++LkDfVpvj5iVCKz0xs+AonSebLsQTzsfReOdt5JRNIS0dMsoSgceIuqvArlXLgppNbCOM1WlE0n+2rgFlieAk4LT5t7Z2rKpRbkb3t07slR3IXYsY58WMAYZk0oYvxhMiVxzLiJs44yrMuOYZB17wjGdM5JKHTvV5Vff43fk97ELGB8MjvjM/w4NbCIoSBt5oRueckEvAMJpsY1urHx8AOJ4HXP2niOVFQH1+6nPkNJT+2QF0ZboQpHcQuI2amua9eEv5bIVQ5eZ/3jAz6HPZdu4B9AAO2WQs5eJ6CcFoSUuOKF/SnvONDrZlDXg4J6yrk5xfBUwvCcdvEPB8db4tGdeWdRM2WAJ0EHAqkFFsFkNbIOttXlbUW6uARRhYGOFxa2/iysFJmaFzMBP6HByFbHg9PRQEB1uoMPghglfjdpaDApO1tMOJoWc/acnep4EBTXFJk4J21QBaSwBP1sYoxZBxfUMIlkSkZHrJ7YJ+zCNezTvkytgla4vEILjez3h2dcLtOPfWTy4jPpuvcC5b9T4Eu0mzi1msxS7sBvQoOYDuGGF2V6VoFoSoBkjT6J2Etlrw69m36SerZ5gI1P8ehcyK0FvoMdlxKBKM/pTEugoOfFKf04coWN6v9pzFkJw6CpAJsiRgsg1KLgL5u/V2LH2MJubAilqtTUnjNsPNa0RhwW4yDmoDwTBpV2LKc4SuAWFfwEOxWepFkG6/zxdtxiWaPnLHgjQp0uBKeKNJvNb7AXrICKl28R0pBjAMcRPcj1GAsSDPEbVEjO8fsRsyBtcAPi4DIhOGUNHqr3MxRbjTMkCEvEo29aghmGLUdZzxPJ3wPB5xzTOyBtzLDg8yIFPBg0xO99mhgnETZ7zKexzrgIc89iQdACZnO5xzwnEZ8HCcsOSI05BwPI8o2bAwAPDgwfTx5wswCEY10FgMFaUMXuV7i3+x8CWuFGWMBaBkA1DqvgVNQrjxFrbzoWUNrjgoCN5ZW9cIqdzHcfDjndcI8rlwHCo0WWehyFNlqt9rvdHBVkrAuhgMHASkI+HwPcH8PkFIO5pVojyhlBgX1w98U5GqDsYB+nyRooKHgkZjoZURFkCjOcdQspuqzgMomwcuiQLswvgC5MkBAgRACfFkxgdhNTBXJXTJR85W0bZg1Zg9IGtnhKGiLKHb+oUoKOf0NKtmu5FjsNnMFArOJWGpJpe2rhGLcwX344p9yvho9+AzmopzTZhrxN0y4bQY5yyw4vl0hoBwygnFnVGGoXTunCqBj4R4Apb3DJDUOg08M2QvvTX/ZLXkxqH26lkrsRjS2AOofWBDaEcXLscawFHBoSJ7Jttb2rD2ndyuFoALg4KChwpZEsIxoEZ1678LitK79VasMHNH9qvzzkPKxqEUcvEJAtNqrVyXBjRnGAMj6TmCFgZfrRjHgmW2JG8ccy9cmexe7K/rDAPj98I48x6gpfp+dHYBhWjSq8lnhsvsKnkjulhFq7zzw2AgUTLf28AC+H2KuM1kAVOTO6+p0wH3+wUxbFrIAxdchQXvx0dchzP2vODTcoNZAo4yIlPEK9ljloSj2Nhqzys+kRu8XA6dN3vKQzePhzJW98Gup4ilkqGAj4OBIavR8JYpIcaKZ1+9Nw5u5Q2MVo3/XB27IcsFUMyPtVnk2X5I3sZXALv90s+jocnJ8DuNNkSmK938y61rBrSOIcHcgVIy56QngfZHjCJeX290sL3kl0GB9Zng7puMcl3MhWcxJx7Zw9q9g7Vsaba2j4hpl1IQyNkstRpNhb9INhd93mY03kFQoBwEOgqCIw0pCnQkrM9p0/VluKIUUJaIOBabMTAgoyJfA7Jz6ktS5GfV0bcWpKmQ0WMIThlS1GIEe1y3eQ1Bz8FM6VvVPlrWdT0t5je57PCwDJjXhPPDCGRGiRXDVPD1qzvs44qruOJcE14ue5zKgKVGTC5IvouWERpP0MEKZBJ0QywYY8HsAI7lGxW02rybVwbPxnmuhwokV2/S184dYTu+ajOs9jOK0unE7XtiuPNGgK4BgoqYnDLkLaSG8CTARC5cR1khiKNAonFrm/lEfhwgx3cz27dpyeAjI6buTy1i8ozEQHUMwLwmAyDNqavClRxQzwE0VdAhW3uTFIMDlsZYUV0+ESxAddN5cf1lxTaC8XlszgH5cUB8GVH3AtlXYxjQBvxh7+jMjwPCWBH2gmWJ1n6OCj2YeeVaA4IjgachIwaxlmeJeKgjqrg/9d6rb6+8T2sywQ4JqE6lWNX46hNlTJTxu/kDAMBAlgDMmvBYJ9zVHUYu+GB8xBfrDnNNfe9YJeJcEk6L+e4O1yumMWM/rngcC9Y1oqzWoWvI4hQrSmVkl8BUJa/+PTlurWKga0M3IBWPDceCzf3romXMwQWBgO7gE527rIURdxkIQF4ZYCtqQNpntk1Hu/kRh/GPyGLvD301lKuSBbFb6UIG5IELAMA2R+m8TCXf2G3jf1LY+OxR3UDAi0t/PYOe01hdw8JnvFHMPcjfE42u4bsEaDFLuP73AVbpRZNW6zKPwYPt7DPmweaZ6rxgCIGSgTaaEhSqu9a4NCX8YhpjMVPmNWFek6Eqi4ljEFkLefOirHh0MYulWvvnelgwhdKpP/d5enLYjc92cZEKA1fZ2jCPxj/mAtRgycSlXGX7t89F4DcLyK3DzGnEgq5sN4wHYRF3VLmgABH5DN49fBucv891nULUKR6NqgVs3Ot36+1ZF0kcsLWPm9BFhf28ZN/sszFJmzoaCoPGjDRu4hENhBRYIOoKVNWU6pp36mZ0oL3j1ZJDFEJYCHVHphB3cb339wwAK0PYnYqEoZlBzstXALly980dYu3vq7vn+OimSTY2xG/1v8u6AbhECRWMiS1wfpJvUUG4Dca3b1Z6RRiRK3YAHngEi3WcmkJU0zUmUgyDaRJfDasJcISKI0wFqgGVGpp7OzfUEd/SOlECY3gA2z5wMX8FTMXqss3bbUA98b8Mxg0096QQ8P20IZhVNyCXCWII3grqTzP87lwnRTcRVzG/0yroAvXqNwmvBBKGrAPkuiCO1WzwVrJqMynytbcg2qzPN2kZqFNHpBgHjoO5TqApJPGFAo3PHbXxugC7QJqFV2ZQEvBUDTylMFGLoD3Lxr5YcM2mcKJiBgRYzEZLG8o3Kq5uZvNvVML3v7iGfHcHeS9jdz1j98GKGCq+fnOPq2gmBUUCPluu8Nl8wPcfr3AzLfhgd8RHu3tchQUVjCKhG0G3eca6RiSXuss5mOk7W987zHZe8nPZpCwrQWvYTAC0VbIMBGvPLcVcUXS0WZZWR5F7QtRchVpbH8lE4vMSQWwbmMwB5JsRWEFHa8XpaF2GmoM9lzsqaTVgmspmqv1u/eSvdMcIP71YYK2mbCSZEceCmGoPbOWyVcl6EfjcezZKp6rkGiCkSB4camUsjyP4lW+zBMhtMcEdaoGUugsNporla7rR+1r79IvR8CfPVrt2g0LPEaeHBD0UTLcL1tkMDk7HaQNGxYoPbh/BpFgcDCViTAT1qhcAXr28Akhx9exsQhM14VhHPNQJ3xhe4sP40EUrAsTlGc1G77N83X1rgU11yv5v7/+UTU99GrIF3hywhoAcG4pbuzf24L7cDSHdEoIm/EFM0NVa/Xyd7Tifo52LiwqzBdXg8+KcY0cvMysOV7PN3d284BKVXqt1xcjxLzY6eDpqMo1ldA71l1lvdLClmX3ehqfIVZ+PNqs6wAKUzsH5qxdt9vYfcUCSB60wOhjJNVIhFnTFUatNSQrAVrVdLr0QpPCTbNW2Z2Kd4mPPcfm7LSCZtKAiRIWQV2uNiF0v0JTU3re1i1KQ7uFIrk08RNMz3qWMZ8MJu5DdPi/iPk9YqvFnR69md8H8KxeJKNi8JTuFwG/oKp6xX8xAGr1H26ycYaVCk0wEtvPy+szj4vuGBmwOKT2B9Mq1HzsnnzcECCk6crCh+NtziydPFC/mMko273233pqljL6J1hwtsRPqLcInMqvAD3Ip+cllZY5ALTFPZdu81cZSADrimf3eaZ0XBbokKZJs+wUuXsADZEPQA7A9iy1QrRQ9CUVP9ttzt+pS+31lVVl/zLUlW9LQqtpA8gPCFfayjJMM3SS+/X6R8KQqbrPb9hWDuJiHv/22f8jGeW0Buh1+6o/7nNoTepO8VCjUOMw/Ym3VcdsTHP9CbgwRtkq1LdsjrFPQKu1L8Yr2+azFz19aD+eNDrbX/zHg8YXvsG5AUK6rtWV7exk2gF8Zu48ZZa9YPyq9OiV43751DiajjjTeKJFVn8g+j90paA7QU7CY7nzOHlzaSatWidr1qS7YEDC+ItQBqF/bqm11Cyhy1SQ9FHBQ1LtkN+ShoBnXa7W2DoJVZ3SMNuO9LUhDwZgKSg14OI8Yxgz52YL3rs54Np3x/nTELmQ8SyeIEr4zP8MX8x7ffnWLm/2M/+HFZ3h/OOJZOvX20FkGPJYBHx9vAAC344wpFsQgqEK4O08ocwQtAVrsRqjPSj8GYAMlaWE/jmyfo8lY+uykwed1Z8IC9iDbPFqtzY7BKg4KAm2CFUmhyfh3JAIMNpPFahum7jy7KXajkRJ0X5CmgnxKQGaM34/A3bvK9m1a5Ssmxn8+TgjfnlCuBLgqqOeIqrCZnl9rl6tLMjpFrxQ2LIMwyskkXgdH+4cgGK5W1KlaQCiMtMsYhoplNklDKQYA2u3X/vx5jagr902/3/+VoD62on3B8CL3Fjb1lqd1xAafI885GqCrJem+VE0WEgDGGzNH348rhlBRJGDggm8Mn5skI4BP6w0e6oQHmXCqI749PweT4FmydnIF47P1gFfLzgznSfHyvEcVRgrmHsTRqEUy2metSng4jchrRPQZdvH2dzNDWNaIacwY04oxAYHDkzk2gE6DbO3e1q624xn8XFgLep0jWAnF5/TDUEzmckmW8CSBPkYoAdP7Z0SvrJXsvJccrKvniOR1DajrW2BEUCdsfrMtuSHd2o4+t20IV0mAutQWBe38LHUJPw0wXlXhbU7aMimmnlHZbKdVTl5t+gyx2cG16voyRSNWlMnBGZd9ftI+FO4JcWuJk1duAle8Mi4unONn9oGWNYZgbiSNmpBSxW5ccRhW7OOKxBWJbY6SNZjPpJrP5D5l3KYzRp/NHMuIRSKOZcAqppUM2Ix2LoYSbKAPkNOq1D9o26BaJl2403GomIiI7GwzQ2ZoVZQQn6hx2Tlp1oXakaNmseXPO6hl94s7/QzYjndHZ1sLm/qs3h8Ozmku1D1x3623Z3HcLPFM4tUT61aENi6mPK16VNyecqybXB8aZsCu0zYvtTbmFqwlNI1lE7ZQ54mqzyHbIm5AIHttaydr5+cSmytZShcJ4kVbetsMTbiiBaBSrOVp7Vjtoy24/2upAdmfpxkNZI04is1mK8xYALB2cQ+IknBfRswloSojQp64HLXjXC+q6xhqpy5Jla3ybOeHBeyVfLs1m9+tHXfa5ucXn79zcMtTWg6zC4xEK7BKcSN4FwYRbx1zUFQHm3ZDlwtTevG9vgsotdHgl1hvdLA9/XRFOA/QUYHr3KUSm6CEVDIfwwHQJJi/Jp0/2wbfJZtmKVzsArNpDscHNmGG22LXbgMskEIDb2YDBAMeZUJ8CNaijq6AxMAl8oqHivnr2VogQN/8iWDzx+bP6u0g8kBQk1W84cQoN0C4WlG8jcrXGRTM+otJcVqSwdvXgGnMfT67C7kLe9+XHRYxM3kixc89/xzvjUd8bbzrFe23Ts/xat6hKiGQ4qevvwBgfN0sjIfH3XaBR7GE5iFZ1To6yGCotkHcR2BQ6xoshHgkLHtre4fPE+CbT1PeauIWFI1DG5Ppm5q1oc+5g4KfL6h3A6ZPItYbMbqXH+/0bAGxYn0c7DgtWzKjsJtcp4ISFHWMoI1S/G69BYtDRSkjKCjKi2wAoyjb9ePAp+K8+aZpbgYEBVe7BWsJroNsyd7+Zjbk8hLBQRxxDBCZITxgM768RsjRrntMFaiE5ZzsmnZ6UZwyTqcRmgns3Z+mMsej0d+mVHrSSwBAClkChIDiAhcN/Sw1oB4jwkNAeS9julqwlgRUQo0bIno/rXh/dzRvWkk4YtzayhCMnMEk+GB4RNaAYxnx8XyNbz88wxTNQezSLQywhCFXxmke+9z0aj/jxf4M3QPrEHH3OPl7tXb2ECuYNuOAxu0vJXRq1bwkqCf8DAa74UBgweMyQY6xZ0/yrCJGwW63opSA5Zy6LGctAVIIcagm03ndLA8FVRjL7NK3bHu05NC5vT+gD/9fWW90sEUhYLLMkMmCqML79KSdq9ppMa3i9HlrKcGCQatifbNWMo3lTbhee0uJgvaZTtc8ntQQxoNaUDyT8Tcn6TNBbZXVYJWo5GZFg+21QxPHp60FCvsbvTScUqfHeFJBLJ1C0FRVjGtbMbAZDrTZ7HoxzE9OYH8+nnCICwSExzriWEYwtJsRRBaMF1qn3dy5ScaROXkgG7+47pvAt3+WYJ9PhSCDogBdD7ruxWbPzmnr5vG82Z814Qup9GTGLcXa6eutmBmB+Plo4DI/1wAgkwLV+MxoFAxvCZaDwJB079bbtGqTSvRAGxykA91QsSDtZuyt2mkVT5vvtip2XWIPzKqbrKB0QwDp9nDNZENHArEgDrVXWk2v2QIobByl2z6kYlVgC7S1slfD2zzRkLL2fg3cYwyKqt5ha0BBNR6piLVnW6A8lhHfWt/Dntfe7QLgM1ruCGTAul27lJ8a2yvj/mQB9OYw+95EvdpfS8TL475XvuzMg7ZsduwAJP+M82mALC6mk5xKCWzdKj92bRYOJQPHxqa4pZ2bHJo8pHcqOG2mDq3ruKyxz8kV8KBsXUZ7T0+t/H6v9UYH27AQ9KCvBUMYghewapFbm+HiD5u0nxBoDmZrN/lcEDCa0O1qEoQnP0QOWkrJ6DwQa4c2GUVKCtkJ4n3AcE+oE9lcpwageiuVFWGQp88LWMsz+JxoUOhqzup8lR1lK8hIULJA2S5OClb1AcB8GjqfFEkwHlZMyfxqVwl4LCO+fXeL8zJ09N83n3+O5+MJX59e2XNIwufrHp/NV5hCxu14xvvjEZEqRBlSjRrUkI7DUDDGitOSoEsCLVZB1iuvUnubzpOcStB9RT34uWIF34iR0O8t01feAm5LQlrQ7YpS0QNyZtAgCNcr8jEZknlXQYNVFSK06TReZ+Mkz9G0rZ3SAQD0fEX1OdK79XYsIts8AYCT9OvZ9HUvKCisEFVTf0uCcdqCStMlHhwFm49WKcJlXOtF+zFGk/c7ywhZA8LilbLafnXYLR10mJsYBSwwtgqNJrOT08oQtmqv8T1NcrAie2LQvmIUsO9rMVXw1YJlHlCW6PdgNXEItf0qJ3vduzzhWD7EV6c7vJeOT45d1oBzTb2lfAgrPtg9Yq4JazVd5KVEnF9NQCWUaXWeviUdKVbMS8JxmRCimHa0f7UA2rbr6rQkFUBfDYgnRt6bYYD5z3py4/KJ1V+n3dxxVzCMedO69nmyjugCF/FCThMAKhmVcT3bHDeNfl0soVuCSmFkWCL0ZdXn3uhgW64reFddzN/Rd9UcZ2yK3oJnP4pAJbCDZ5402x2wQ6t7rqrPB4dt/tiVZciBUV6xkYsjKCvqXrDAFJOYbC5CxXv8SpDymlpRm906torgPFsh6GA3V6ukNflcxkEVlgH7c7VMjhWcBIedOft8vuxxLnYTHM8jagnY7RdMySra6zgDAB7riIc8Ya4JkQXvjSfcxDN27oZzXyZEEtwOZ5xzQi0BNJioRYPpS2pXuLrxgrflXleBanrSgAFHhIBmPMA+cw/STQW64HgSk3G8eC5OgmEslmn6Y1D0zQpO8QlRUAZCnQSUGeXVsM2CWwfj3XqrlqmKSXfMavq6TbzAvE5dTN/pOjkHFApdCCJeCP5Pt0ufPbYKTrzN2eaXBmtwURWy0RKH+oPWlTDvVFoY2FeAxR3DyACHYgn2ZeuZWbppQfTKbVlib7WGWBFaQ00BtC6Yg8EAC85TzIgk3UBg0Ygv8h6LxL4fFA0W2JTxUEZ8/3SNMRSkUH12Sxhvlq0y9O5ehQlVpGTJTc7m81ty6FE2BMEYK0oNG7Yl2P5SJwWK+QNzEHCAqwFqpxXlNXYjGvvMYi15oV6cNFnG9nNg061Oh9XayReVOgE2ZriwQJWGRXkbKls+ZIS9tVikuiBCIai2ygr2xf6vUm/zUgG4EOpOUQc/oQR01x+xVi0P1QbijRpA3Fu+vaJuVVxQ6Cgog6lV9edrAZbV5sOKLci286QEwAJLmBlcgXJLgKq3LkyNCaReJTfVG+qJgEH47WK9mexCv18mnHPEWqIJphcGHxT7lPEiHRFZeqb6cjkAACJVfDA84MPhHoBlso91ROKK67TgZbCqkUmxSxn3bJJtkrTb5/W5eSFosRuJKkFH7WhvFXRnI3LTgqYgRcFI8cGVs7qZgzaHJDuGHIwgL0JYAbPoU0uK4EAWArxFaG1sPjPizKg7N6Qf5GkC9G69FUurB6/wtFJVR8YLq9tFKqZ9RhXu1pWEgDSUrg0OAC+urQJ8mMcnr9NcYapsnENNtn/EZLNEBbaA3Nqix4D4SMjXxQRyHlKXY5Vieuw0VYTRrN6GWHEGeqBXJZTVjE/afuZyHdvnBxB2do80BSYzjBeMjaPqXPxTGfB8PCGSgMmEO4oyHvOIu/OEZ/uzWfc5pef59anPa1W3JLkUxsFtP18+7lFyhMxhGxENgnXnlCJPZAhAdV49KqGWgGm3PnHrESF7rnPsSXSMBuSqpwhUQp6ojxItUd+qXj1F8MzAPhsKmS1ZWlcHUzl7hUhRVsf6NLGcL7He6GAra8BuMF9JKRFYGeHIqFfVADmrH4xdtspwcfRfACQClWxeyCtBrgz2jVMwjeKPR9SdILy32Ma9mKBE49kSa6807QHdAny1G0ERgKSQwUFWlcAPAWBA9htxfqturUURFksEsthmAAdG6K7a5ymmNtUCvxRG+tiqy/yVbNWwMI5rwmke+7zo6uaMQIqv397hKi0WZMuAV+sORRlMgufDGc/SCbfRIP2LJMySTHKtJjzkEQNXvHh2xGFYMYbS5z68uhZ1oyi19orPqa1b4Dy2lqjsNhFxyWSt4MEkNO1vtM9XSt7mzXYc3GUJ6ACUEhjqMx7AgizU6BSyWtDXQVGi2kw9KDCziV+8W2/NqpXBo92DeY09oaZgym9tdMHJ7p0xFVSh3mUBrJpSoHPbp1hQ/dpjVkyp4FQZNQdkApCAOgdLMMdtllgrY7mw7LQAXCFXFTn5eyIFXeeN4hLEBPHdXQgwMFH08Umz/RsmS0Rr2arx3o0Lm1qT4VVsTlwkYEXEF+uud7heDCc8G844BKMCtQT9Yd1hH1f8/IvPnE/L2KfVK9xoJvawAJWm8sRhZy7bTDTsnd7kgTW3jkKqG6p5qpBolM3Ox1VCZEFxgFd/LmryjP6Z3cpUvXBBJtSRUEK1djQA2hXISNAlohbG/mqxTsZnOxuFDeK+2WrmEEm2xP9LrDc62KIwYsz94qcuXegt1UqbUIVuCYjpFxtqmGeAGwjqQmginghK7K2E4ELZZNfDJa3kojJtDhMmkEG+sZuzTNPoDauJasgBW5AF0OXjxPScqeBJNa4R5lKUXZjDQQ+AVYPxSAAD2Wec2SXS+gXIwNW0YIoFL0bj2xa/YV6txo2bQsYhLngvHZF8TjtLwiIRWaxtVMS8KG+mGWMoiBeKMcZjxQb5dU1n483qRttpNCDG5mPZDkMxcNnlam06om0G1nnH7V4i7Z60Iop6sXmpOue50EYF8xk5BYEewztRi7dsaSUEF46x7otzwHfSrfOam1YIbdZHKC7MIEK9xZmCgQhb27VVp803ts8VFXYNFgIOT0E6zfUGALSJKYwVSqZUBADDmPvzE4mLPHjlpiZSYcGFe2dnHEsHGdHFXgWljpto8oTtHhQQ1howu81mBTsKWbEPhm14LFa9rxJxFRe8GE54lXd4zGPn2c4lXghkqFeLiuhm9g1pTCwuWrHth7Vyn+MahUfdvMH25LbXNkW7JhnbkpEuy+jPR+wqe47jaHry0ua+1b3BSVBP0bA2sHZzODozxceH8DkzAAjzWxJsYUi4yl4F7SrKWEFLAB6iyysqAqGjVJWB2owCgqKO1lghp/bIVTH5th1Dk2mmhKFCnrlgoVpFDZ8JwCs1KIyzOTPSPSNfGRm9keKb4UG+Nc4nnbyC25dOWQJggf4IcAbOmYFQgevsCiawQJ7J6EfsYCoBzj+bQUlw/cxaNy/vDmZgPWYcJuPaPh9PmELBVVyRJeB3H55jlYBcAz7cP+DnDi+xZ7uZvrfe4lhHfHy+hijjg+nRVKWmiocy4ot538/BzW5GZME9zCSgV6WuXtXbxop+QbfN57JqpaCQ22x+tMlayI04bk4p3u5bk83XDwUhVYg6NWBJVsn6edLKyGWwY5upJ2NNz1oA6EDAoUL4y4mJv1s/OauJ0IN8HtclGVtCZ5SZrtoGYIgVd48T8t2IdLNitzPwj8IQtJEMABTYKt08MOqOu+l8uCrWmnZ0varxy9krOHi7N7IgjQU1ctdBb+8hr0Ytau5XFcDp1Q40B+A6G1fUBTZ2UzZt5iWAJ5vvyhcD0heM8nMz9vulo32r8+e/mPfYxYxnw4bZ+N58i1UCrtPS28gA8NXdnb0nZdznCZ+f9xhjeWJUz0RYHbnNXE22sQZUoe5a1FSkzO5QMY3Z8vULkNkPnD8x1a4yTwBrNwxoHsJMivN5sMCdBDTULiSiHLqgTggCSk4trGSWiT6fl0tHNQGadWermNcy9FHY77Xe7GBLT8UhKIjRTJZgIvgXAvibYIK6YD+6ZVufu8KqVivM7OYTYbuJkrgQNfXsqN2c9gL+mFe03fS9vTd/GEmgZPrMqhcZ16WKlWOLOqQ9apdfg1y8hraIQQiHtXvYLjk6ed0s8Jp7T/OqBAzRvIrxBCObHd91MLBUowotNaK4HFviCobiLC7dCOr+mEOoqMlUr1SbMhaeVu5+DJ4oe2HLZrs4eNjk0boeKoXegr58To5WdQDoQBRyZGY/Nn68yGe57fhesAysnXcpEPBu/eSvlrw2XAehA2Iu4bB23zkDgC7uddkCcKOvtCquyZkSqVW9F4BADo4ovqCwtfdDMDOOtho6t9bQ29cNgKXYKEcArGLO1sER0a7epkBH5feA7V1jZkPwNmJP9tnnKgEjjDMb/H0LrKuVxcZgESZskUhsv6jR5B/hs2k/lkxqHim83be9E9mP04Uft2NXGsf16e9i00bHZluqvu8KKxgMeIchsCHCJTPCzmez/nw18oa1eW2famIlDdhm1EXvVl68l9/veqODLU1bP79bLlVDjslgPXYEdQF/2m4i59W1FiYBXWhaWzsxKiBAvRtQp4rxYBVfG9BTJlMscjUXWQP4FKCDYv1asc3cKUYqW1DmsUIYoKO1H9hRu0oeTAuQrwBeHVBUCDQ4SOohmTSjokP74UL/05QxeEYZWMChYj+t+PDqEVMoGIKZExzLgLt1gijjdpgxxYyvTPcYvbJ7qJPxbElwnWZ8dbpDcBeeT9dr/C9ffATA2kKcFByMChFYUD8fzVbvKwtCFFS/husSjF7RFLvcKKLPxVgx7VY095NaLQsehoIple4stORoZ2s0kYuGJGRyMfm8AVvaDdgcf6ianKfsxTxIFzJRDVcCkvIu2L5Na5gykJKhd5fgCPpLBLx1P9p1q2oYiiUnpKEgfmBz1cCCOUcgRyQPMEUYrEbhIVLsxxW5GC91dJpQq9ha8GyWfipmTNCceIgAmQ3cs3pyILMZllQkkM8R+VCgUwU9mrAMXRdQFMxzQlkjaA6oAM40IH5wBn1F8Wy3YIh2jzU0NLPgnM0eL/p9DwBfme77sWua6qKMRRnHMuCxjGBS3I4zlhpRvUgBgH3KRgWKJrjz+XzAzgFS5cIN6BLoBKAnCq2IOKodm2bHNx5WQxfvzcZUX44o+wq6diBlowC1sSI2/1+a7LmlEGo12mHcmSlNXu34dvOJqwpkQjgz6sRPla6GCp2+3N7xRgfbRh5vwvztoGrjrbrtlFzAyi/76010u13ULRPsJqrqM77LNsZFJorL/5K7cTSD8szA6kMDciQeATZodJoMNTSxVeWqphlntIBNZrK/p8sETMhmTP4Zuxaov9cYDZ04eSW71oiHPCLXgF3MSKHiJs04xLWDoWZJtlGQ4CosGLngOsxgEtwVaxsn3mTu7PW4ow81KmTY6MrtHKEaoAtRrQW/snGQQ6tqmy2ZgauaMXa7+aJvdmu5qCy80m/k/k3nElti1ToMLSX2UcLrM5bfjwrMu/WTsbroyuUX8KRbpoBzWgniiWAzG2CWjuAtxSrP9YKqotgEIi4r3a042FDHTxa1anSjIbWuV0NJX+5BzQMa3hmSdn0vjhFpbVofnRGAYagYk4GtqjCCz1AbB/XSPAAw5ajIAnOPNiGNsw5PKvlIFavGHrRba7h3A7BVsg3AuZSI4jzh1qGyW5Yunmc7fiEIJFbUZg7jx7/NXYmsoi9LNAGLxgjhrU3NXJ9UpW1/QiXozh6TkyG4+WBqf5RML0Ev4kebF5tF65cTxHmjgy2WAFEx7us5bC4/DkpqqizL4jNWr1axcpdslMVUpMLOiNLCJkJhwvU2EG9KKwq/SZvSk2dNxIKQgHJdTLN0KFhrst/152nOHxrttfXKkMXymICxIo4VKtZSLgcFRM0Hli+I09EMr1UBPrM5CH20YJgsoBbhnlG2Oe0+rng5H3C3TPjkk1tgCXj+tTu8dzjh6zevcBUW3MYTvigHfLLc4ODSjr+w+xgvwiMA4EF2+C/zCwDALz//GHd5h09O1/aayjjlhCVHHD48OvzeHIcaFYtWAyMwK/guYnjFmL9SQLH2RGc3ZJu7rtGN6W2+spaA/bi6TZiT/Rc290Ld2seqBuW/vHmgVgU3k2llBacKWfhJcK2ZUZc3+1Z4t35/q6wRoLgFMMAqWZ/JmcQhoy4BtTDy3iqwzc5RgMH2jOWcoJlxRxsqHjAz9hSqe8oqVNs1zD4Lfjq+Mi1mS/JLDij3A2hxUX2CsSkYPWnkVCGFIXPsYL94Y2I86T/tLPn9OcM18I0pzYWgGFPGlAoeZ5Ni3A0Gftq55V4VRhYDT+68c7XnFYkqFo2YYcApAEgk2IWMmzTjW8fnuFumzlKYS/TkXbvqXIzWEZjnhNPD2KvHpmls9EpCLqYUNaSC4J2tw7gCI/BZjqirsR1EGPXOKFF6qMDC4O+PWN4nV4pyqdc5ohJv3rSytZ9pZRM22jOEFNN3EqgA5581kFoYKiockxPlCX+aQwW+5Ajqjd9heubUAEsXJ82yn4uN123eqF6gA/1X4Gi2hqLleVMhEVbQ/oelof7zljU1+cSWAVGbCdhGT22O2IZFnnUB2xwDBJceRJ8pU1BogVGZ2FxuEC+oNBdQ/xithTxGC8D3ecK5JJvNjgadvxpXHOKKfbAbqPlR7sKK5/GE23jCNc+YKGPW5D+zGzFXk3IcuEJAOObBbLL8Aq6VraXTqkrXim7GD8skKHs/Jq1tJtQNr9uxuHQpaeT2nCOkso0HgD4bLsXaSn2mQ+qzem/xA9CBn1S15C1mqWRtxOUd9edtWlLJ4laQ7ujSOiGNX9muo5ZsA+ggHL6QE42pQsJWEceLSkeEMa+GEo5BcJrZNb63TgyATfWO0BG1za+5sx7E97BWiSfHOZBcYE8EBEa+9qqumm5wE99oSOtcg4nuwChDbb4cHL+xixljKB0IdZKht4/LE/9aRVHGOafOu09cN49fYdydp95BbH/TTBQa7abTBL2tPp8GcBSMDpRSfWoqT6woc7Lj4/oDFEyiV3aGG6mt49WKHhgFEECnehmNUqHTZi+oB91YLJfL93U7935uwF+6KfZmB9ugiA3tW2EBiE2PWJWhyW4YcvKxOiWHstFLLo2gVWDgBAfTDJ975WgUW9Bzf82LdlM7GY032ippwG4YUzNrd5O1fGixTV8jrK0z2M3bkJHEm2pVGF2dhgWyBMQzoewA7Kppfnpg72YKpNDJMsGrYcFSI16e990J6PntEUOo+MbVKzwbzrhyQNRd2SOQ4L10xM+N38dPp8/7TfZQzIzgRTzijnZ4lfdgUlwPs1XM56lX/SVbFYCHaBvRdUZz7omDgbXyswVlF60FXshbc4r5wgnAkge/KRSd1L4upgwzXPl8t5qAuKwBlGwGbwHX1KbaOZFgeswb9QEdPKWFwacAenwXbN+mpUsAHcypJ7ghSZv5N31cZkMJt3FPwxa8vq4OM4gUa7Frdkwbsv24DJjPA/b7BdfTYvq6c9iAm9Wq1cbtbViEGAXivM8QjQtaXg2g4roAk0JH6+bEWM2AvgUzFuCrZ6v6ThGYCqbDpm9cvQMWWBD9fVsbOWMgxYvphKu04ODJeIDgk+UG55owV/uM+2h+1yMXHNc9Pp2vcIgrvrq/x1wjVrEZdq4Bd69sBDXuc+f8H6YVw6Hii+MOy2KKdG2r1MLgu4g6CZZbA4olTxaCC4GoEuTzZG3mF4sfSwLtBXTlIhgXUo9Nc0EkbclLU/fbV4SpoIkDyVfs+cj3nstFfMFLhrexXw/KP2K90cE27MoW3KRVNejepQVxqx57tel/rA6oIWztR88YNSjyjXPgGNDDRbtoDpuVniOX4ZwtDWIBm0y/tCECt9dVIKpZ8DkthoJ0T1uKAnJnCSh65RqjQHcF+Tk9QTgDbQ4CSOPs+XkfQsUpD3icRwzRfG5vxxm7mPHh9ICrsOBUx24+8Dye8I3hc7wXHzFRxivZY9aE7+bnOMlgX3XwzNZu7LlEnJehz4V6dnlrNzbHdlztqxPcg0vPKaHOARI8A/0hKD8iIGerlJvUWnTB+FrQDbfZ4fgKvuhYqGuoErCEPgMHA3XnN4wAVDxZe7femmVUP+uuZA+SDTDZOjRSuasRlRQ677MU46/v9wv2Q/bOzlbRbpZym0Sjwvxb1ZM88oS63+ude+73iCfZBOfHsgCjdDEbTYLggTZGMXOPxqeF3SsBrQoXs8JbIsoSMe4zduOKGJ6KQ5xXq04Hr2gFLq+owdvJFdeeEzeU8iIRkSuej6dezXYKVKgYhJF8zJXSNu5CseMznwabkfoIkIdq7fFrw9x044B+bJ1bHCvqVdkqV+DJ3l4eTOpSb7Lp0btCnb15x9UsAcihH6MGUmsuS7Kay5h4oQS2IN5a4u24fVn1uTc62I673CHlBsv2arOZBBRT99CL9qE2qHklMyCfLJAWCVvAZUW9rb2NFEdDHWp14wLvDiNaO5QyQ6NAJn8R4c3lB/AsiLb3Ym8EUA9OHpgpmfmzNPK1r+io2zoUrEtCPW9VWCN4vx6FI1VkMWWadDD6z3vTEc+GM74+foEAxSf5BotEPOQJ76dH/FR6iRueseeM75QRn5ZrfHt9jkXsMlklYm3UH2UsOWJdoqEzfaNiFhxuLDNcc7RqFxuQoYlZdNrFyt7l8VZzrADoSUaZs7WJp93aQRxraZ8fCFw3B6LqN4YH7xirgVoWA5OpK+eoK1d1r9t3wfatWiEZCr0WNoOK0SRW21hGKhvH0uekde9ausGux/qYoLsVu5RxzglSuXfZgO1678jaBiJsVDTHjNTG0RQTu4FuLevmhNO9cadqAhwA4GYbMVakUCGSIGJ7icICWyCbeYqDuPI5ge4TchLsJ+2m7laVByznwQIkVyQS1z42mt8urDiQdh7+SSzxfiyDzW2HE1YXv2FSxOadHQl7NyIYYkWpjKWbPTDkmBAeGXUvhkkZYRziYbshmdUxHH7unLPMV9oxIk/oWgKEh4DxC8JpYpu77ksXD6EomHYrzjICYl24EBRl8U6X2yuu62W7n/qeZYIm9njT0f4y680OtikjkGmUnm6qOfNcIIp1KjZzefSWZAMcDX5ik/RZic6uIjR6ezaI0W3OAQVAHgLCWCG3Fwhiz4C0ARZIUZYIHCMQpc8We9sS6EL5TZxfvfqlwVojtRD4LoEqUJ/BaC6wbKpky7TAgJ6jtUeeeRvs1QAwcPOVB+zHFacyAADSUPB8f8ZHu4de0SYv4wIMdfxhesA3hpd4Fk6YNeFYB/zb48/i2/MzBFJkCfj0fGXcWpKevQZveZFnfq0t3677nv1V6nmHcWAFkmgzFWgVsRDyaUAYK8KFWk5r2wSnGGWnC2hhKCmU2UEWglIcNLVaxro6l073TeqSu25quznLdbXxw7v11qyyRAiSXQMuD0pAn/PVs4Eq6dqs3OrdgJoEuFkwDAXhg9UAOwDOa0KpjDEVBDZlpFwDzqcRTTZQxEA/FGxM1KQem5hNswkNrrLUzAzabLiNUzgCujdOe+soNbN6Zu05YyAbsTWlploZ42GF7HKnH7W293m12WdKBuQ6lYSZIpgU7ze1OcdlZHcea64/u5CNBgjFUQIe84iihlgeQgVQbAZeA5YSQNja7KKE4fmMeh0ALyCaHnpDLjfd4nZ8W/dgVcL86HvcLvdjBdixWm4K5hDA+4KYqgVkglspGlMjp4o8ue9vMVcnxA2sRVEMpbwG26N3peuzn48DNDPirnxpzu0bHWyHUMFkGWWzn9raxWoctKBbq6ZpGT8RtNCOGqbMZtHmmqVabcYqUR2eLgg76V6o7YapLp5v7WMzOqhXBEp143u2FgZbv5vUtJabHisFWNZaGXE2ucZ6RdBkwaYCnZROrEBxQ/Rbe95wYmg0VG9iweKzlSGaecD74yNu47lnpqKGEtzziq8NX+C9+IgDFTzIhJf1Ct+en+E7x2d4bzpClPD52eYuV+PSpemalN0lIf2HZnmt0gT6XIqDVZntOjWwEwErQ1wEoMHrWyuhURRai6/TqZSg6vNyveRLE2oyKz1KYpZ8q1OqGsCFFDoBKu9K27dqZbK2SLSWIjUXLeeBw1Xh4pQNOfxFMvpPZYzDiuf7c79GSzW3mTEViKLTgeoS+uYuwijOt+e0XasbZc2u5U6BadQSr7QB9AAERpckBC4aaLThEhqVpwUnZsWYbJzUjAFqf6+WJA+D4T1Wib29XJUQIChgVGxz4QaSGi+U15pQTnakMqO4dKOBonI1qdcUq9mbKuGwM8OUu7KHVkZwF6P2npM7IhVhTGTfd4qVdwXC1dZqVj92eV8g5AlE8A4G0Kk60T1tc1MObEm9I5+b61Nt7AbHfzQVO12Ctamn+mXVGl+fAP4fX3/37/5dVwTZvn7pl36p/3yeZ/y1v/bX8N577+Hq6gq/9mu/hk8++eS/6bWK6/UybTcMFKBdAW4so2GWTps1s3c1t6BdcUlAm5PSvkKvSn8OcxHaZgFE6ND/OkfIYlJeUDKB7SROJwDqlSEJLRM10jmSi95nBgo7TUmhpQk8KPCYEF4m5JuK9YPSEYjMriTjFxcnAa4K6rPSb0D62oz0NTMHYFLczyPGUPHzLz7DR7t77ELGLAmf5Sv8h9NH+NbyAi/iEV8bvsA3h+/jGZ/wSkb8v84/i//7538SL4YT/m/vfQt/7PApfmb/OX7u2Ut8/frOEIpQLDUisGA3rhiTu5/4DbquEWuO3Wuzzcfn2UUEhBBTwTAWa0G7tFqIgnCd7SboVmeEfByQ7wfMa8K8JpzvJuQ5WkYbFLryBnbzRUlA0YBn9RQRPx7AD8GQ3ACQLckJSZB2GWn/zs/2j3L9Ye4bAIBBEJ6tSNcrhqlgHDOG0a/JqSDerIi35ioTYgV9ZUZ4tkkzbjNE44Gn5EGh2pglxorpekHyKpLZZpgxmnlAiOZFnW4XhOvcI2ZzmwHQLf+W44DlYUQt9n0+Jqzn1I3ogQYiavdTwbwmnPoMtuJqMoDWYVix5IT7xx1iEDzbn/H1F3f46vN7PNvNuB1n3KQZH4yP+On9F7iJMxLXzrN9Vfb4dL3GYxlwrqab/vl6wO8e3+vCFmMw9anIFZEqrsYFh3HFvn059SgGwfE84v5+h3Gfsb89d35uXm3/aK359jmjH8cxmpBHuCq42i24mhbsx9Ueb6MqNtef5KpdUhj4bES+M13n/bTg6tkZu8OKccwoS0S+G5E/3qN8ugOxYNxljC/OmG4WpKFgHAoO04rxdga/WDDt1t4p+L3Wj6Wy/eN//I/jX/7Lf7m9SNxe5m/+zb+Jf/Ev/gX++T//57i9vcVf/+t/HX/5L/9l/Ot//a9/369TLzI+q/4aAMfBBV4tkTiAqonWX8D37e/RPXAvB98AoLFVQV41XegYtxYoBwEqb/D1KBtsvGWb7fv2O11v8yIvqugykzRWo6RcLs8aiFzcn7d50G6/9AutVcGBBbdp7tnnuaZuPrBDxp4XXPOMG1pw1IQH2eGu7PHFsseH4wM+SveYJZm1XlxwJrHMVTeaTmBFFc/E4R1ybxfZm/N/GgiEmxuH9naZqsuOQi9+l6EknahOZRMUMDGPrWJoNWmTzduSpO0YUwEo+nloVDDgSxPS360f//rD2jcAqwyTJ+PNhaaNPlQJGjdTASLBMBSzcVzSD1Qy4eIauhRxGFKxqte7YtGlGwvQW8AGuGLU1UYhDQVt4i4u36jUZzOEbaYL2N4SLl5TnbvepQaBbgwQLs0ShCxohYIpFAgI55I6JiJyxc7RyICNnMDmxmMASQaw2eytNSCyIDqw6lLwwihE2r8PDthq4CIVskQhVCw5QVzqlXkT2nhyvFvV7h2CIW6ykjZ2cm6yt9pjM3ZwQGTrkgUAKazI1ZIkewICF0CDCW202XdLsoZYDXA6BLPvYzHA65dYP5ZgG2PEV77ylR94/O7uDv/wH/5D/JN/8k/w5/7cnwMA/KN/9I/wy7/8y/jt3/5t/Ok//ad/X6+zlgjCRebT4lvrLqplnmEhQ5sSUAdCclu+UkJ3ogCweT6SB/BdAR9WxGgWW8s5baLTrx1gVeqKTjyZgpScI3hXuj8rCNBsf0uNQ+cXpVQy6zfVTltp7U7Ag5PTEC5fuWYDctxenR2BbJvBs/3ZAFHpZMbwZcKn8xVyDfjG4RUOYcHX0hc48IIVjE/rDf798hESVfzizSf4KN1jZKuGqzKyMlYJOOWhq8tYcANO87CZtSsgn432Pq9snkFDBUdrD7UNxTY19BbW1j4DWthlNoATTRXKinxO6JrHsCpAFdD9hY6sG26r62KnmwWaKvLoaERv6/PCkMHmOPKQoPdfthn0bv241h/WvgGYGfxutI14CBVVN9WixuW8XGMwwOE5lS640vAE+8G4oE2u8eSc08gGMqqTzS+Tf13qLFcxaUb7/FaFNQecdn/JfvEKunlYW8U3xGKJ60UwaM+9T40XH/r92lL396+OyPszbscZU8gXqlHGmW/0HsD49XsYJ5+hKNHQya2NXJVwHRdcRwNFihK+d77BKQ8YpuJuYhZs22w5kuC+RDycRlxfnbHzQAsAa7LPZMfBfjdcBOomkjGEihunXO1TBkMhIGRhVC8+sAcO42ogsIOi7gj5ekYKBhht53gIDNGC8EK66hcBXUyH/HOWGhBDRWLB7W6GKOHVaYd1/XJh9A+8jQwA//7f/3t87Wtfwze/+U38lb/yV/Ctb30LAPBv/+2/Rc4Zf/7P//n+u7/0S7+En/7pn8a/+Tf/5kc+37IsuL+/f/IFWPbXdHOb3q6JJTii0FHBChiFJ2Cb1QE90LVgC2xQ7vZ8rQKzQAGfC+v29z736AYFl4VSmx9fLncX6Sg3Un897khoC8LYtH3be+v0pIsZDusG8oIlIAr0bHJxL9pjGdxYgDGGgn1YEUhQlfGq7nFfJyySkKjiNpy7OfSisYMhRM3Gqyr1zakrOF3OpV9fr81ymz2W0XcCagkXAXj73U7rYuNDtg9JF69zOaf6AXcQP3chmPEzSJ8og3WqEeHHdCe8W7+f9Qe9bwA/eu9oWINLugrwg4GWSTti1yoq+3+upnWcffNPDt6j156rVWHtsdAeowu8AumTa7jNW+1LPbBWn30CKVbEUHugvVytu9Naue39RJ/ftsqyVWvNaESUEb2TtDq9rzjzoII94Q54rCPOdQAbyQ6B1EUsrGpuRifAJuVq/yeccsJaA6R1IMkqxV3awJDJ28QD1yf2nezGBKsfdwAW+FoC8tpGS3ha8QPWhTuMKyZHaL++XwzRNJj3Q8a+BWlczsTtfy3gN034Vij8XusPvLL9lV/5Ffzjf/yP8Yu/+Iv43ve+h9/8zd/En/2zfxb/7t/9O3z88ccYhgHPnj178jcfffQRPv744x/5nH/v7/09/OZv/uYPPK5KPVPUc7Q5zFRQzy6a0FoLV6amomMFDbLNEukikAYFyYWA/cJQBtYdAbuM613FOK1YSM0wuAVkZVQ2cBO58YAshmRjNzFWoAfN8caI7eV+sPeXrK2pzf6tEjS7g82Ze0u0lAA9RbP9a8LXBOz2ZtSsSphzxLwaEW6/f8BaA757vsFcE7Jb6QUWfG18hQ/TPbJGvJID/rflAzAUI2fsecVEGZ/kWzzWEd+enxlgAgpRxjnHPh/N1aXnuvKTn5ib4u11NcTwHKADgUYghrK1zkqA3JvUGu9Xg/GvwUAM1BCZTupvAiJCXW7R+JCmAkXeOqKpGgdxkN4i7OYH54j4KqDcVtAzEzEPQZHeK6i7+fd7qb9bf4Drx7FvAD9677AAaNdtVcJaItZilQuTqSo1ukrwCrX9XRXG6sl8VcLNtHTFtqYTDpiLDmD71FoD4K3KS2BTroy1xI5RsJ9nBEZvbw7e0j77vd0C8SXVqK3jPIAI+Gj/iMi1myG0VrGoqUedPfAFFlwPBnq8HmYUCXjINtMcfPwUILgvE84y4HdefQRRwi8//9iqXl7xquzxxbrH8+GEmzhjH1dUYZxLAlHEECoe1xGffXqDtMv46NkDYqi43s9I3lJ+XEaIAjfT0lWp2rE0XA7wcB5RSsDVfsaUCkbf+095E8RpLmbFQVVLjo5mNkrSNFmgfVwGBLYWdHa7v9ZRaOenFRRzjohs3c1SA+bK2I8rhlDx/tURwjP+1//qVWjrDzzY/s//8//c//8n/+SfxK/8yq/gZ37mZ/DP/tk/w263+296zr/9t/82fuM3fqN/f39/j5/6qZ/q1WFg6SblIZjbDFWySpZ049l6BmIbtCnGFPZ+PhwR2ytMPKGHNA1fZoEEvjAHMKJ6mw2DcZEKbdmrzt7EaTawTbaxzWMuKtbNpg89YSBS03YGIEsw8nezl1PCcR6234NlvKtELE0dhsRACnHF83jEgRfMkvBQJ9yVHfZhxZ6sFZQ14K7u8CrvcCoDigSwz2sBuwib0ERrpQk7xUepo8KJjNKAuKlkSbi0Cds+o8jFnEkvUZibjrHCjjOvDHlt1qrYKFmXFXavkv18atTecbCqGhbMv1xy+m79mNaPY98A/it7ByygtqBam6erG7C3sYgZZHDnybafN8N2wO8HD6SmT+6PS+x/c1nxAui80bVES6QrQcCQIP255jX19wQYv9funWTyj1GeVMWA349s92rx0c/AFZHdyxWuHBWeou+3Ct/mrpGMawvAKltv/VwN1tK+FLUAgKnJuWroFd/9MkEBTLEYqtkV9h7msQe1loQ8nEZz+AlWgVsiErBkO4albHZ7S04oNXQt54auvrQ6bJ3NlsAU11oe3eGo0Z7mHPvvtvlsaUlYozvlgOoz9na+WiK2S9lkfr/E+rFTf549e4Zf+IVfwH/4D/8Bf+Ev/AWs64pXr149yVI/+eSTHzqraWscR4zj+AOPd4RaEPDOUK3DULDq6Abr6u1B3/xZAXU7pjWAVkbhjctFAcACQAnUZq3cIOB+kwUXsGBXoFLa1KIU5hLUMlQ4AEcJ8VUACSC3DkF3qTBeCZI8CMDa3ZQtUqn7u6qjG9PVivw4gO8D9D1D0QIGWjh/sQNIcfXeybNzxVIiPj/v8WJ3wvPphD92+BTvpwf87PApAOC/rO/hs3KNz9cDeDQa0CIJjzLhO+dn+Gw+2AXsKYPpqdqFOz+M4KEakjgIqAVgadZ5HvSDAnszzNaVIZFRq7oONXU961J406ZW/6cGSEVPOKTYc6QjoegmrQdYEK4S7FwIeiLQqu6YCnQCaiFzHBKCniKoEMpVga6bnN279Ue//iD2DeBH7x3is9JSAvISe4LcsAXFtcbb3rCu0ZKzOSDsCnYXso1rCV2/G0DXHl7XgJqDGQU4bqGtJRmeoXpnSHKAeUFb0F8pYj0naGGsPvIwzIdJGZaoyGMrMlpGqZgOKyILTtmS77lEIOGiVS5mn8eCpUQLGsFQw23eu4sZ+5i7Hnpv21LFH7v+tLv/iBLOMiKQ4oWLWhzLiEiCfVzxrS+eI+eAacyIoeLDF/d4mEfcvdojjgXjWDCvdo8un+1AlXAfpSvErasJcWBlk9y9zhimbBxXJZSDASatu3Yhv9uWkjNG7Lg1wFQDuol3EVtxk6+y40Coy8Gq2L7DSTaU9BKwpggKinp1Rixfbu/4sU+qHh8f8R//43/EV7/6VfypP/WnkFLCv/pX/6r//Hd+53fwrW99C7/6q7/6+35u/WzCUiJyCZA1dI9IcKtgLmarYgdWC2/VKwA9RSyvJqOkNH5d3YBSrepqjjR5jQZKujhJ3e4pag+QeC3bDCtM29hVSXSQXmVpAHQw8WtezTcxnBi8OE3oImtDUOhoFfi6JCxzsgF9fYo8nKu1VsZYcDue8f5wxHWYsecVWSNmGTBrAkPxYjj646FXugAwhYJDWrCLGXfzhLvzhOM8dDFvYu1ITlVDgbNXsR1kxtbObXxYyYyS4wbyao9X01XWxSXTuHGgrWJugRaFUSeFjO5Z6e11WU1FhoJRfrSSubWs1qJrOqlwdS5dGVRcG3Vhk257t/67WT/OfQMwvEe/LpoueTMTIN2SPr9QQxDEVLo72KVVnng1m4tVYrmGLkphL+b/kqKeIupDQl6iCy20RN+pRNXeU17jhutwgGWjEcpeoKO4B6/6z20UFmNFDGLqcTXguAw4rgNOxb7avhBIMMaCXTLBilUiTmXAYx5xLgmnkjp7IWvw+S0bKhmmJrdI7IIWooRzTXgoY9dGZu8atkryvCaz3UvScTJ5jVjn2A1LSmGsa8QyJ0gNaAbxKMYE6fcxNscv8i6VfDGaslfdCh6OYq83GjX0eDdhPloiwkERprrtCd5dK2tAWePWFXMzin5t0Gasokoo8uX2jj/wyvZv/a2/hb/0l/4SfuZnfgbf/e538Xf+zt9BCAG//uu/jtvbW/zVv/pX8Ru/8Rt48eIFbm5u8Df+xt/Ar/7qr/43IQp332PM/6PNWuBVk8hlsLXf6/Z2alrIiNJnqOGRwZmQX8DUoyqZpKODoQieqfoNIEvoVSwaYEoNmGWWeOoax68N588WcHUJpljjxvc4w26YJKAjI6wAZ3v+OgHK3If5DS2tYwWcP9opRd4+TdGAE+fibj0p4/3xiJ+aPsfzeMREK1YNyBqxSEIgwVeHOwBP28cAMMWM67jgWAYc5/eQV98g2oVMdnOva4QK98BbVsvyG/GeWVGzmz2sATUbYvvyGInfTLSYL24IzRzCMku44AUpoR6MxwyYMX28Dyg3gEbpG2Zd7W9qBppyTLdZzAzK7DNymATn/C7Y/lGuP8x9A3D94zVaoK2WxDJv1+zroL5mnTcOG7imtSgrm0BD9kAgzpsPQVAobEBMUugxIMyETAodBWln6lVtBNKEbbquOmvX/Q5BIYHQIEhN4Kbb9MFQvDHYrDaXgPk8QITwmMbeym50H8CARUuJWJzOJ2qIXgFtghhBe3erIZfPHrQPwSr8Ril8tez67wRSVDbOfBOjAdApV6rmPWvWgbqNdgBIbprQ3iHLQM2EGrf6sFYyswg2n+zxs4ByRajR92APiMwKJG/DfzYZU+HFihCtE3rMO2BuNCSzLOx6DQSXgvWWPbYiY2jXQv0jaiN/+9vfxq//+q/j5cuX+OCDD/Bn/syfwW//9m/jgw8+AAD8/b//98HM+LVf+zUsy4K/+Bf/Iv7BP/gH/02vtTxXHNQNkvd28czHAViCO/vgKRrY57Y8VWgxQQmRsM1lhcz/VAn1wYfubBSgdDCKkEaBiku5nRwYNF7IMjaj+CRmDlDtBpw/lE4/UrV2lSZBHV3gQgEZ3Njg4P+SQgcDWOUcIMcIKlaRqUtO9tnuYNlbE7U454SbccZHuwdcRzOA/yybB23igkQVz+MRAYJEBZ/XK3xvfYaHMuFcE27SjEgVi6vJjN72atJnZYk+z4h+00t37miWZOspuWKOuRbR2ig56BtbdU3lZiigB5gQubhPMJmeKSoByTxB22eWhv5uX4onzi3aOLUrI3yarF0/WUIFcSOJaMhkre+Gtn+U6w9z3wBslMR7GzNpbUbgGx+Tk0Aq4XwcQawYxtJVijZnL3S1KKAxIAg1G8gvJhtFYRBwtKAoVwUysmkxu2+uCm++uq3KDbgYY0mnwTXdZsUF+9ATAwWcp2rUoBgEVwcD/t37nDSw4sSpI6gBWHC9SAgSC0QJ9+vUj1czIPlMD/2xSNIpN1XJKueSOquAWTBEG/NVMVGbhnEZpoJpyOChGsbmwte2MTsMFwMgCuqNt+jnAJoqOAou1bbCWLF8UAwkO1Zr/1ZCGpw+6B2E823pjBV1jAhFgYwuE8nSaZmdfeLrksXCvM3g27H7vdYfeLD9p//0n/5Xfz5NE37rt34Lv/Vbv/V/+LXKtYEMAimGKWOdzZWHHBmMtuECG/E4mEVTZYWwXeTSQDXi/Fch0Cn1olWi9puRAvlzGX8XCtTYgE2wmxeAOk6/oZv1mff1W1XI1nLW5C1Woa0NPRiBHMUqMVVzIaHFqnDKhBrs97vQxWAk70NaUYTxUEcMXPHV8Q57zz4f69iD5z6s+Mp0ZxZaJPi8XuFV3hnsXwJ2vGIXMj7PdnMNfsGqEmbAxb9pE/IANrpU9JLUnXZErT1Ppc2hXWw8VpQYPFgDRLYBAbjgPCuaHR7cjhAeUJs61fYGqPNo4TJsWqyCHV4R6kRYAwzIpoCO2Iwhvtz98m79mNYf5r4BAFICAuNJ9dqxGz7+UGXIKUJZUWM1ZHyLiWSGJqrw8ZU9rj5/pSDQaEIv1IFMirCrkMHtIP11DZ9AjivxUYgH2UZPI3JaUlA3QIeNX3QThgA23jo7bWg/rlhLxON57EG7VWjtnq69U2WAsCFld/VKmELBwrW3hlvH7DrNAFsQbmYFS4nI7joEGNWGnU605Gi4jaYoN1i7OwSBJiuY2mftmgl+b1NUUKzmDlSoV+jtmNbKZuJ+i95Rsw6cfR9bVRqBclh9Rt7Gc74XO3uBW2fySTZzEWj795s4xx9ZsP1DXckDkc/uQhTgWlDO0eZ77QZIrujkF7JUuyBCFJSxQonB5wCqjHpVuyuMVgI7/UaEzKz4HEC7ChozZOan1mzqwb0ZFGQG30dwJpQX2QK5/2qZI5ANWWtArg0QRdFmlbQEaNWO+K1JUQft1XZM1WyhlHB7ezJounPA3t8f8Xw8YR9W3JUdjvUZHsuAVSLu1wlXacH/Zf+fwRB8XJ7hd+f38TuvPsLXDnf4qf0XAOxG+u7pFueSXFTc4PdEimm/YpkT8oODT3wjAQmqt2Fal0CLtcRk5x2AurXZKGi/KdpMRGpAXQ1x3VrT7e9QGeHIkEFRhwAaK8oHuoEgyI5P/38U6EAoVwqJQHNgItk2Wp65dynerbdjxbEgJkKlgKrWKmUH6jWbOmK17hFtFdea41PVqUtcCKzKQiFoDVjFMSCZUEaBDORtSe3+rOsarf3bgsBq+BMIAYeMFE3XtwqhBkPlrg8DKCqiywSSj0kI6Ajl43kEEXC1WzDniOWcEFPFOOXOz70/Tr21y6RIg1Wbz6bSsR+T+9bepBkM7e1jwFrQ55qwC9m6ZzDt4nNJHUEN2FaQSzBt8qiIU0ZZAz47XSNNBeOUbUbtXUomNQhKMApfv093Ln0ZtnPSjznMxKDpIjS6H3lLOzfUsSO9Q2qGAuNmCNMM7QvbnlUcVHXIPakC0OfrRRgP37+C3n05qdc3O9h27iVvRgFRUHMTE2++sxZsG+ipi3yzgILNCKk6CtiFMXqLFkAXrihWVeJgOr4lth6uL/IvH7hDCJwJnPFUllG8AmuzX7HqtAMeLn+vT+ktiMDnESFVpGSm0grtvK9GvdnHtfPkmhVWI6kvNWLgCoZAwLirOzzkqfPV9rx2C61zSTiXtLVMHJWdYsWCtMlPggBypZjim8pQXbAj9PlTk0psMnONNvS0NeeZ/pOqFV612nmi1v4LirArqGuAZtrOg2fGRKbEVQdsFLD25c9LFRef4916GxbHCuYIYQHxJtMqwoY+9Q6LWUJuYisqBMSnQjhtSZvztuvP73FyHr1W7lVuTyL9fh2GinUFqoZtfwA2oRegG3CgmJQpLl6K6QLEA6e6kHbEtVaCxI2a1w093NPbcCoBEmsPtJE2YYkdr/64UaFMrakZDihGLjjEtTv+iG4z30v/V5DvnTlY52us3dBFhYDgwZPghiW2x4nYvc7teAij+WJuIjjtyymXvtcr0JOo5hHeePybUcwWtNX3ZHI7Q/LzJO2SYDztNp7/O6H+/FhX5m0W8P0R+boC14tVS2MFHQdQBfTGOKnt4NY5gJIgxDb8F0gEQgXYATqYMhCshcxj9d6+zVCDZ1Y61d7+AbDNT1ugUKDceOkrJqpgtB7b+Eku/hbogVpdtEF3JsIRnHKU3bVIa1NuUuz2zYXHroTHPGCfMq7TgiIB//n8HgBg5IpfOHwft+GM63BGooqsEd/Nz/H/fPWzYFL80otPcBVXfFH2uMs7RyPahbTUgOogqOAE7zxlY0oVaw+JQ/D5MUADwId8wW319+4XdtOG3e2cAO8IwWa1Z9949uqCH23Va9cjPUdr/7gRhDazeljXQgGbvSuh3m7KNn2bbACXg0D4nevP27RaFfs6R1KbqEwPmrZn5DkaEKYQ6r50wBSATjOrcwRIka6XnjS2liU3GdiLgKjqYjihdXY27ALSdo/Y7NIsNkXIHcv0ApypTwIo/K2LMB5e7U2Qf/RKeokYRkuK93tz3Fld9H99HKBCKNeMLAFLifhw/4DdmPFYR6ACL5cDRAnPhzOYFLfpDFHG5+sBkSs+HB8RSXAqAz6f96hOLRpTwXC9eoVImPYr4s0Z85xwPg0dEZ6dt8vJ9uxhqChFgRK2hONsnbOmjSzuEyzZkqS217fjoUrIjwOghHCwcV6tBsAKo0nrqreVW1AHCTDae+Bg+0ptkrSkWGdDi+uhouLLUX/e7GD7enZZDd3WEXqtumFYFesDVbt4tz8jslmpRIAKANAmmt8H94Ya1Da0aQjk14Olv4/+/zaTza9VauQtZ4YF3UzQYQNdALAq9rKN2m4uz7BFLHtsWq1thgMYeGGRgLVGHMKKQ1zwfnzAi/iI98IjqjK+W57jru6w1ogpZlzF1W6yahKNq7dcGulfFBcbBXVHlNo+s78vVju+tXBHSjLZOQBR7ywA6LZY7Tk1Uw/I7dyYwAi6wbuG1867HxsC9eciNu5vJT9uYbsenlgxKuw6SvKDz/lu/cQuA9fxRTWzoYtf73wA2BLA157jieSf2h8/sZ2EANErXr/sGqVNxKluUSG7C/Rzuz59Manh/9prOd2nvaSKiVV4SbY97h2iS1Uk9ABkwKXA0pWuUKnbeL6+ihuQdPlFF2l3L5QLtHLzu5YuMNE+Q+O4SuVunzcjbUXKa6sF17ZfXPLwgVbR0sZWEOseXHpTG//eW8KvP79XuZeCR+oCJMroccRa0eyJkW57tIOrePhyifobHWzD3jK0YSiY31tB9wnp5Yj1fbNekgCQOjAhKEKoqLzdUA1ur15FaiKklxFYgTyFjcMGMzyuI1vMFGvTYOUNiNWCgsDaD9ED6eCoQ7YLXIetakMlKDHCHWO4J5yTAlM1IJBuQIm+PNA21G0WAnYLAgvuzoYcvJ4WJK5IXHGXJ3x8vMEvP/8Y39x9im8O38d74YgAxSvZ4f97/AYe64j3xmNvE38yX+PleY/rYcHgcmiAKa2ot4aqmmJVjBVXe7PzKtl5sqKoezHBju8P0ADIJNBdxbCvCD5XMWAG99eloJCFQY/R2jSs3XowXa2W0T6kLTiygcIAQx22c6rFRC0k2nOHq2wttGWjYLRFnrlaoP5yNlnv1k/GynMyuUavJhuqmIMixNwT23xha0mOQGUPGu2aD03YJUoPGq3tTGSzxJqDA6dKF4Ypa8DwSYQMwOIIWi3cR15SGQVWwakSVhffiFPplbC4HCoIqGT3xKW2c5hMHa3kgDQWHHYL7u73kFPEcLsgpbp5Q8MC0Lkk7GLG7f4B+2hgqbs8oUjoe0Vxc5KlRCSu2IWMLAEPZcKpJJzK0OUO2/w2xmqfu1BXw2JW0GvBSiqjLAFYCLUm0CiIY+lt/HBl5gnMau3oO5N8xc51kmvzwUbXT+CTt8uvnC5F1lWQcwSNFXGsm8Y7PMn35Nz4/Aw8JshUERwvA48r8jZUtg012C8uBrwL0e30lLYq0Noy1Csa7cHrokpt1Y6gz26Jn17AT4wD1IIrAjqyWP29dFOB1+eBZNw5AQMF0Kiok/3NJZG9iWp0mbde2Toiz9WlmrNHQ94xmZRcJMHNOONZOuNZOGGgigDFCjZBC7JZyy5kHMuI789XeFhHrCWC3RHkSINnyXYM1wsC90Yup97KAeyYObj74lhv1XBkwVqCURRcsaWhEqXxo9sNIVYdB8g29g4Nlbm1pzsv0udkkrkHbC0MOgeriNPWHWgdi5KDZcfv1luzNDPgKpBEtkFraaA87Ztsk/1piF9RgBN1EI7kYMH2gu/eWpjdVKOhatnEVoqErV09OOWv2nWKlQ1J79QjkdCT004PatgMwTZzjM5gEIJi4+SHWOx9EDrIi1i7GUop3MFE7V49Z7Pa27l9HmsDUW1VKy4f81KzKGOpEXNNWNw5iMkkGZtpSbPi7J2t1/xq22cVl69sN720vbo1DfvxtXPUWCd9xt5ogS2ZGtXm0pcFltC2f/h10DoFrUtnOB8HW8Gej2nbd1ql/mXWGx1s2d0wlpygq4lFlPc8u1lC7zJLtgzxibtPdcRZq3Zae9RBrJStHRHGihgF7K2DdpNcBtBwJtQRoOelnyT1tgZWb8u0NmUlIAJpLMhkIhn1SlCv/b2tDKQG92/er+Im934RVQLvBcNo6i9ltRsmRnPBiCRYJeLFcMLP7l/il3bfxU+nzzFRxqwRL+WAo4x4Hk8AgOsw4//z8FP4X19+0D/TVVrw4fiIu8V2pJb553MCDxXTlC3bLhF5cbEP56UFN2AgWCsZJ7vMWqUag+DhcQfJjDoWcBDspxVrDDjLU6J+zgEpmcpL9tFA2JVeYbATzJclGr9xZdBCEJhKFWWjaA1fMMq1Ir+fOz2IyGa7+W607PjdemsWnYNRRVogmyPCQ0C9BWjXWpQ2OzRwpAXCcDTGQn0mkCaGsiMw157w1RKebOIAnLMpNm/0SosIqB+tFjgyg+aA+MDIzxXxqmK9H2289L5x3K2CVejgWgCZTaClELATxKEiz7EjoDUoeH9B9yGTXI2xgg+Cmq261sK9Y6RCuHucUMWcgwSElcKFa9BTXejkATiLiVqcyoD7xZT9hmj7wP15sk5A05uOxjIIroNMpDjNro3shg5mVhK64p6sRqfisLXEa7Ewr7u6jQXJ/jZnM6PhvfGj8cK6dHUJ1o520ZAmdSmyObyV4mInKxubMJvkroZNsKhxdEthyPLlwugbHWwBbJZYpL1vT4WBik1FqjAEQOGwzQdbH98t77DaCRAHITVk8GUWZjMQV6HyljEAt+67qEr1IogHL399g2+0FT3YyZXms3p5b66eK06ABtMJrdXmOwjmbNNmLz3r9Yzx+XhypLHiEBd8ffwCBzZo+sf1FrMkvKp7VDD2YekvGdntpVLGFDMOcYWA8JgHnJYBTQmKLjLRnI2mYPqiMF5wI/FftNvUDZvtGHp1EOwzpKE8MdKO6WlLqbVwRAm08pPHS44IsSK5J7GwdTSaYhiCdrB3OSjq6LSqi5ZZE8agHzKTe7d+cpemLQARKZAEdW9VUtfTvZz1RTFxhT0AhgU1dW68J6Lars/BNufWzmyjoK6IVMnEXRiOTgaEjOJSBEC0FrIZeGz3TVut+dZmjRodSEgmxqGsUA3eRo2dedGCiQU6TwqUTMrw4vKXGoybu44YY0HiiuqVbHQrPfHvhRRZNju+SJbwNyelejHXbg5rT+h8r61m2nCped749ibbStAEx+R4qz5IB6/1IfJqdE4dq+E9SG3L5gY4Ayj68WpGMs711TlsDmxRoQm4BKEB3p4uDH4VER70Bz/ID1lvdrAl7fQROBKcCiM8MDgD64emKILFnCUKvHUY1TbYhbsdm5wMKazjhb5xfL19zF3aDVGA4ubjg13wDVF3OVulaPNFPUXQwhhfMspOoe+bQlKaDE3XbkxVAt2bQH6NAg3GIy45gGaGHiqG/dp9YE0dxQIHk+Ir070pSNWEF/GInx++j2SoL/zu+j6+KAc8lhEjF/zCzuzJHuoOu5DxfDrjG4dX+Op0h8c64lhG3J8nLEvEbjKR7hLc+acw6kNCuI+mUxwVlG3epHs7NynZjIakUSJ8Y6oBw1ChWnGYTPEqV0YgxThlczrpqEpFWW3eFR/ZkpoXHoTnANophljNvaVacOdq8ysEBY0VWthsbJOJCTSJPvUWEDml6N16e5YZjWwVaBwrdJAuG9qEVPjo44fbCkoC2lWrjk7REnJnKtQSejKoe1iwXgI0iuuFXwTbKFCyfSTGpkxHJjc7mtyqVEJoIi4wBG+LsJc0OUQLro0nTKlCI1Dg4CCf51IwjeCUqukns2A+GwNgt1/NzUwsgc7nhJUj7nnElAKmWHB3nrpP7j7aPcuwCnf2inbggiFU7KLNMD89TyiFPZm2ijOFimnIKDWgVH66v6p1sppaFtCCoCXly+Nosry6BWD7bAoVBeWw+VQvjPhAWK8ZGL0zgA3wqmQazWkoxvEtQGM/hIeAsAAagToAuNI+wiMvqnS2/fjwbQa9+nLX3BsdbLVyb2fYAbT/1737TyY7uNqQyYVd0ciCs+79BiIXsYiE8BigRJBrqzjLYnD+mkqX8kKbK7jVHhXfrFtm2xCv8LY0YFKEQXH+ir/2ORlfNorNFxfeZsjBA77Phm1uKdB9BTsvLYwZZr5cEFhxs5uxT0ZAT1QxcsFtOHnrOOGVjLgre9yVHQKcsO4/+6xcIUDwjcMrvBiOmNiUo45lwGE0v9zdkM3zc42W1d8ncPVWVSZgJUhCn3EB2MBPK0FH8pmRzV9S2PRRs1gW3N02vA0fXBMWAGpQlBuf6zS1nSSgi/lvA7qVYPw3ZEB3sI2vCYb4tUBiZgSlMNIDg+7ezWzfpqWrOfjwWDEeVpTiAD82kB8c+Sr7ahWoksu7+r3eEPGF0XsxzuMmnwleYgvqapaeiC4H6OVuY09wUJQ5gh4idFfBOwMEES4Qz06ha9xRkAO3/OVN2KeCGRiurWslvYtDnbYnXnWGWE04wi3xCoBh2MwMmoXdWgNud7MFypARSTCGgiwBr9Y9Bi54Npz7sY0sGLjiejcbXbDd55UR2Aqku3nA/Dj2gNkAR5Zo+/gJQJpKT2b6ymR7fboYrQGdRy/C0FGQb/245NCTnWYeUNW011dvAXPcqmmZBGCyIirpxrn29qP4WFABnD/cZv+/13qjg22DliuwAYoA0ypu/XXaAhe8nalecZJzuYjU+FaBwJ/bIZFrGABhDVZhKm1KLW322+gksOftRHQHJFjfwsBCPFQ74Qc1MM4xWvsiiollLFZhkQB1dwF2cPUqZlNo4mDcsjGVLrcWSPH+7oirtPRAm6hizwsmynglezzIhJMMONeEq7AgkCBRxVFGvFyvMHLGN3ZfIJG1oA3oEHEYVuySoZAJdrGumTF+wagjUCcFn+19S7LEpiWrwe0FuZDThrwirYTdkA36n6NluRc3kwh5S8rmu8zGmzsfzLHJWubqwVg3MQHADB6iInweQUImPMLbF5Pa5mhzBQBAeiTQ4x/89flu/Xe8CgHZOltTKpjh1WMD1Cjs2nVeZqeXePcGYRsNNbBQ58lfFAAWSAWlRNDMwLXpJAus9akuaUq7CqyM9EDIwTdw3WbHALzTtn3b/LVjFDNJqYQQ7R693Z8RyO6N6t0k+xvFaRmQc0AICubazemrADFUjJP5uqZQcc4JuTI+PDziKloAZ1LsQjZWQh4Qh4pn6dz1kwcukEC4GZb+mlUZp5wMc8piTmV3yYItA/LcaITi82OBJRLTlJFzcHlYWNXq96124SF9WuAIgUaxVj0Aae5KQRFdOappLmhl5/RuXUxNPpIaq7WaWfvnEDGwFEcrnsoL2CjwS6w3OtgOY+lVDbGCjgHjp4zlA4Jcl21eQvCT6ifEA3GIDslvG70SypVnMaxAZnOUIUU5cJ93ND3SdrM1JBxdzlUygwssg2VAn68IyV6zAKh8cWFEhe6rgSSEPINF567GWJGz+Siq43j2YzbjYiUEFrw3HrELGScZwKT4KN0ha8T/f/0qPi3XuCt7BAg+GB7x1eEVElW8rFf4fr7Bt07P8dH0gK+Pr/B5OeC+THgoI1aJeG86QpTw2fkKa7MOi4r1VnsFrqt59eog1rb3Y2mIPyCsdjyad6f6Z6pim4D4XHaTXbObTMTk8ZpzB3t3AMCWhTrwouSIurpTCCm4EKiYFGPjM6va3B7kCZknaOevVujNuz7y27TCmaHPq6kZVfbKtm3o6KpCnXrnjlTxkVFHtYpXCCQEPlqAqDcVaKMKcS9VMaUh8DYnBqyS0lAhxQBN8soCwvpeBUYBs1FTVAgYWjer9ueVNYDOAXJVEK8ce0E2Fw2eGHcPW2FUUnMuc9P12/1WiRJMevA8TxiGivcOJxSn7DRgFACsEnC37kyWkStGrvjm9UtXj1owSkbW0APxKhFZAj5f9lBV7JMnLkq4Psx4BHo3axizBeViHQCdAwQFw1Uxc4cSjEJJDPUMpBU+xOodS9cFyGxmNIWA6wxOJiGrFc71vWBO0KY937SZnxwY1xLofrmkJkICAFCUwD+o9/Aj1hsdbO3AXfgOZkKcgbXgqTxiOxaeRbUTFIKiLBfZKjxgAL1KpgIne2/Z6hOZRd1+93KRA3XIf14bXadVV2SPd/GMwdtDFVuVXuyJA6kxuQpZmyuogYzIAQckOESrahdJECbsecGsg/vT7vFYDX28Dws+iPcAgO/m53iohhwsyhjZbpaHMnXD6Ou4QED4+HjTwQ4UBDJKbwHZ+6UuAtK8d5sVGbkrj0nh2QZSfUYLtBuuuXy4bjILRAJqJQRX2GF2upRenluTUZMmf9mMtNXPQQFMd9r/7fQJ3c75VYGEd+bxb9OiQn0MUYRRXVKxLx819DaNwFDEKyCB7Dpt4Lpi93n1659JIWS/AwffdGEVoPNL+8YhAM8EGQE9lM0TWq2att9HlzYV99zmxcw1eiXtwbZTBeH3TaOpeFAZYsH1sKBeiFRUdwtSNY4+4MhlRws3ek/2CrkqYRcqnsWT8dlJTKBCgOSC8TVknGvCZ7OZmRiwylp+Yyqo+6WLVrT2bjs+5JiKwFuCYh1Fw7Fs1D0f6bF1Jdq+TNXkFuEFUqs9f9BQYDvfUII+QaqiAzcBw9U0loXRQf0U/pD9/4etNzrYnk8D9jeCeU2QYwSuKh6/aYjf9GlE/oplg3S2C0Sni3JfLxxrOkcLIA8izW4vf8Wyp/NxtLZlkG5kTgtb+3RyndILpyGdFDLCNn+/IGrhnkmRC2w/ucFbAGiB3CuyqhfqNt6Wenjc4eFxh29+9Bk+3D14e9Q0SxNXPAsnnMQ+78+NnyKQ4IN4j4kyAhSzJnxbGbfhjP/p/f+ERBUnGfDZcoXvHm/x0f4ez9KrDrZqSlX7acVD2YHPDNkJaCpGba20Hbs5oEZGGTM4Cpb3K5DUUZ72OdbFbu7r/YwqhHUNYILbiDHmJRnZXgnM3nJWk5MTB300r8/QQCjB239iHQoq1FtJfRXqHGhgS7zwX0FIvls/eavuBEOwmWn5bAedKsKuoj4ku6/ZVeUu+Ne6r1if1e43qz7LK3u7z9rY6jJAGw3QaCu0K87RJ5TsSSOrycJOxgNtTlkhVYhZYUGFUSEdNBhTRfWEnaIi502wpalFLSVi9aR1LQHnZcA0ZHx0+4AxGHVuLtZVejGdcEirB01774kr0kV79IPpEYe44OevPnM/2wHRg3IbST3KiPuyQ3I2RPv55+c9mBQfHh5xLgl384Qlxw0ESdolI+tdsjGcdwiK7wGmqewBP1sScuk/LGJ0p9Zt0F0FPy8Wf4XAgwFJi0vK2gsDTfOgS2P6rF0BIDOEbZTVu3TRXOMaP7lr1n+J9UYH27oGBC6u9mFVjQaBnhjhUhDocq7ahtyVoBq65VP/xZZJtcea9JdsUoBa2NpKbX/ennb7HnDUcgPl2MmSpsXKRrDuwdZPPDGMQiDUAT2dHN8qaaBXgpEFiaS7cSQnmQcSTJyxasCBV0y84hmfkKhi1mTqLiAkLnjBj5g14bFOXXZtdFWYVuG2DLnZftmD/v6ibC16JeMoi4EdCLDW8oXEYof1e3UO3rLy1uYxmy3qh4bbKMDPRftB47vZ89jfQtHFMbq0o8J5wP7/Sv3hL5uZvls/OcuSMKueuDyVECXxEeBldyyY/eawyzaymENXeqIu9Xc5ULXrugvkRHRwnoIML6DwToz7Kf+I69AELNp9iL5PtHtKMnfv29f/7pIyFINgirlXukXY95BqWslurbdUU4WaQulCFruwYs8rbqO1n7+v1z/wPitMBAPiYhcqKGKo48Dba2YP8t0Q5slhu9gPYZW0SBOU8HuZAWATG9LLv2nbdjJj+LxGGzP649U1li9R0O3lu2Unbedi26ucvSCMWjc95svz/3utNzrYhs8Thp8/YTeuWA6po3llJyh0wc+apLeBbJbureNswaB73TrCDeTAhMzgU4BMgnCdu1oVPQaEE6NeGeyeVm8rqW/uDLuJopOhW4sTQL04Qcbjoy4GQYPfvK8SqADy4Yo4mN3VLOYuIRQgSbDfL9iPK6aQsUjE77z6EClU/F9f/Bfsg7WIJsp4lk645hkTVWRlrGB8XG5xkhGJKhJVvIiP+G5+jo+XW1zHGb/87IwAa6/dl12vbLPz75gF5XnuNzg5d02rZZfjS4YkoNwEA1Xtam+/tMtynKxaDa5h3KH+Pr+tc0SYilEVHBQWgkLkBy9sBZCSiZ0fzwOqmMCJesLSg2tQ8FAhx4TwyGYczwod5UsT09+tn5A1CPJsNnT6Yu1dKz5kyMjgVwm0AnprQDwaS6ekqBJ0RHcZa+poDcSjLkMaDk7RmzdMSHAeeX40AB8fVkgh4GhUIh2rJ5Fb5KyLzXPTVLzrxsZddwAnVYJMxqwoJYBIcTOdQaSYS8QuFTzbzZ22Y57V7MpO5A4/No465REv7w94dnXGN29f4jrNuAoLrnxM1VrEu2CBucJmuxkBD3nCQx5N/AKKBwBz3e6rtQbMJeLolKOGDiYyyV1Vwvzc2+SnCDlHnCqDBwucZsTASPu1J+ddRARAuModANv4+/Pq/Oc2XloZSIK0t7FRA0vVEnvLHl7dxr0J7pTKRg86unevOjjL7fd4fAvkGmX4wfmEwugoklpK4q2attW3QFdgF2vYspjLzNJmjwoZxEAPwVVbCnvFhB/o1zcgTkMrUlCbwTYNR7UgbzKCXj1fZqOteg765G+YbSMwL1unxgAdbdgkFJkUV3HBRAUCRqKlB9pEggcZcNQBD3WHWRMmsix3loSsAQLCSMbBM8efgGMZMNcIxmZvZQdoM2hQtipUVxMUkWTI5JYlXnrVMgHN3mrVgBiiXbx+0edM3Ty6yWy2z9aq63rZtmmZrL8XNPAa+XFsQ3NuHDt773opldzAbu/W27OqVZfq3SMCup4uETrAuIMrgU0EpS3Sp5XVa6u3lGn7f1exY2wSg8BG9+OLqsuLhx/ZefFRSuvOtPusfZbWFk6hYgwFA1cHOxUwjD+b3Q5v1YDZfWg7RQiEROKAJ+5fAHqgbdiMBRGCzXgAsEA719Tf16W4xSXAUYQQvSXPLECgDUBaCEhNHERd6/5C1tFdlSgIYvO+deaItFk5oTNRmviOmaT4uW3jvH687Ty0FnXOwUwIXqu60Tpzb0NlO331CGAr8TcdTBNZgBDq6kTXaNKLBDuIWcxhpnvIXgCgKChiqOCdIjyTfrGcTqPZaA2CmrxiajeDI+KQFDyVDpSozC7xaFkvny4oLqOA9mWbAWUPTtfFnnoJKEoYnlUcdgseX7jN1hyQx4g1FRyzqbxcDQtuhhk/N36KiSzTOtCKr4UVswIZhO+U5/i0XOOTfItAgj+x+zZmSfjP6/s4yYDotKGRC76/XONunXC37jqZvSU2KmZJFVLBtFsxz8nUz14mUCHkDzIoSc8jGpiASLEbM1KsePn5FWQNyPvYuXIlB+hjtAQkGf84V4JM9lqdI+eozC4aDrtJh1i70lYTN1dPjsg5eSAFjWJdOe90UCbw8o5n+zYtOgUQsytAWdJNbSxRCBiNR5lckKGsLmDjbIS2ulvQRWBsgbUL/Hvbl3mTTgzX2cZKbZxxKJvoRcuzfXREQzVjAvUOGvx1goInowPa+IQ6GrnNOQ9pRWDBPq7Ofy04OD5h7/6zazXf6pfHPVKo+PDmEWMoWGvAyBm38YTvLM9xLCPERzY33k7OGrBIxEO2EVR7jUCKT87XLttobepzsVHXzpHHAPDwuDPZyV1+QrHhXTHKzsKQwc7BMNhsMLvVoGlaM/QUoANhcFR2QxfnHBCSQIJCHtOmFCcEvR8gSex1fCzYEyN3WzP9a0J+GNH0D/pX2zucI/1l1hsdbNc5YamKXE06q3k8dp4ccFG+wP0OW5YFA9D4HI9mm5MK22zmR0qKtdmfKHi2ACqjA6SEDJZOlikV5a5YVf1vnyTBig0d61QjKAFDsc8wu2D5xR+xK8YAwJIjZLKfXaUF13Hp3FrA5iaJCK+EcCcj/t35G/jucotdyLjyVvOrusf/7/Gr2IWM95IlL4vELhZySCb12Li36xJtc/HML4WKHCKkuf1UA3810AFgm0bTQk2xYgi1t9O4/Q7ZZ6s7AzJ0a0FyKzDP1InUkhM/Fs0+EUDPyrW5iFwebPKkzBHePRsVAIGeVhnv1k/80skUo1rDyxx6/Pq6CHoAemLXkjWGV75KqIW6fi85Z7/tPy0ot8ebeYEqOi3oBzEb2l+zd4Z8XNP8coO7gtnf2fNKpc18RQlLDWCvWpvX9cCmJbCSoYtXl1gsbgYfX5uBDqE6JqRizysQt8+UNUCUsYi1VnchI6vJNgLoRiiVBdXpfcAmx7iWaCAjl3utSQBXw7OgZ6yHRnVc19CtCxtwkjypIMevXAp4mDAO+3F3LmzTte/HDtsYrAFTtc3eeWsp81aM9ZFUS5J+H9vGGx1s5W7A/KEh2ZAZqg7U4QuXjJaRKEEXhqiARzt4vFITikG6Z/BKWILdODq4pZP3aDY/SPS2dDxadrMe7ETRwtBoJ0HWYDPf6+yer9HaEJdAIaVtnhANPUuZgGsDCmkhqNeHjU4Tow/+c8S8JJQDI1LF8+GMD4YHPOOTwfA1YYAgEeNBI343v4//x2c/j08ervAnPvgYYRJkDfgk3+L//fE38FPPXuEXP/ik82yLBOPrjg9gB2Ady4B8Sp79mfTbLhUsORmy+9YCcwusYyoowlgW48oexhVTLAgsOOxWrClswIXKiLEg7NbuE9r+jcENFoLJMurCNlOZNk1XceBFGmzOsp7T5ovr1UZzALKWstixJUAhP4hafrd+ole6XoFd6MyCvtpoqKkT+UZumuji1ZdVwSUHC3JHk1fFreEYondYarZuG7d5MCvW1V9zCV0SsnXeEC4CZ92CAjs6lo5m9qFx7d08AlzUwmadIgRhwmkxt67ikq7dxN07VEzawY9tTa4YtdRg+uhhxcQZiSpu4xl7XcFQZA347nKLVSIe8ojrtOA2nc0Dm0zCUZQxxtLnxjbu2pLfZU4oxwS4BnEdLTCGKFBvD5vwUIFUQj4NkNGq+MbJ52CcY3VgZs6XwjjWVYjJWuIcxKz7ThFNQx8tOQoAIK7xbq1mZWxBvaGT2/lSbOC5Bl79EuuNDrY6VaxORqdsgUlx0TI8GbFZbkqn0TRJMIqCeiW9P5+vFFTVzQsUUgNEFKWY68wQy6Y+5Kvs9UmWJDunnzS7qksLOJ/RUGs/NLUpEISrWe4NAmUzXxcxVB9g2WCuAXWO4J3NYA7jijFUvDcdcZ0WfG16hefxCAEjQHCgFRWEz2rFq3qDWRP+h5tP8cH0iD9x/V1chxkv6xUWiXj/6ohnwxn1YubS5Ncimej4gwQEEuyfnTdunHvbtgywgZxKjpDK/eZVl1Js850AdP5amzvDH4ssqEQdta1qn38uEUtOBgAZxWY0F9rVtXLPfpl1ax85UpODWnKq3jZstljtPMUf0cl4t34ilznIGPa+ooFtmlsXQBFbS1ibB6r29qUFXAWxt5yTbewcNopO69407fKSA+o5GigyqAnkt+5LJWhoPqwtg7S9ovlu+wUMKX5NDwbWWuZkyX0hrEtCrYyUqqtLWXVahbECHQF8iXURNd/ZtRj9LrhNZ6PuLGLlZWM52GzWPuM+rogkvaKN5JxURefmHhcDRB3G1V6nMtJggbj5zeIUkRGhN6snxvbeFOZFTUswvfNRe9Vfm4KX42TaGKAJ51wqcD3pVF7szXKZkEfD6fDlyMmvFZAXPq1z4eYrtbBJ+n6J9UYH2zBW5JxsQy2trOdOt+ETg1dgvfLsxMFQKmSSaftirRwh6KH0OQfI1Fvg1IDgVn5tmN6G6LJ77QQ6L61v5HFro+LyJlKY2IIjmGXyFtTghG1g46SqCVjUyja/mAgpCD7aP+K98YjINmf9+vAFbviMVQMYgutwQgXhpYx4kB1mSfjjh+8AB+Cn0ksIGP/L+evIGvDV/T1eDKd+AwHAs3hC4opZUpdhiyz48OYR55xwXIY+G2pfyTeX9TQ84Z5dVqn93LFd2DEIGsCYyb4nIU9qGCLoXLt1NTQiD3WzHXQQyPEUUZYI3q8ILlxeKyNLU6TslQABAABJREFU8/71TSCIVbdusdU6Fc1q6916OxazGWU0II61JLFVPXQhywpsAijSuJX2MJEiOH8/JkPNl2JUk3ThYJXXaODKhY0ad+UFQPXZ0iXtBG1eC3Q2A3z7aWA+NmWjWgLqGjrHtC5WbTfvbisSLKBKNQWpFGpXmALQJR1zDQikPdiOXFCVkTU4BWizOSu+V1xF62ZlNZGaQNZ9AmyM1ZIBYsXtbu4Jd4pmSNDayfnVAZwJdc/dp7u3dFcGnwk1stEMW1JUPFA2MRFWVNncli7XD4wFG13rclbr8/lxsvlxzgGKp4k6O1i2UDTd+hzeDou9Ju8FUpNnPAeTVwzG/awvCppouGYGH4M51NxughKdhrNGUy1pAAV/PE0Fw3DB5RVCeBXBGcjP60YtYRPQAACom5df+uV69qURlq0GQMk1kIOaVd3slTj5HGEyMQjAIfK7alQYFkSuiFxxFRbsQsaBFzAJPi7P8F54xNfjPV7JiE/rDSoI12HGs3Ds89xZE/ZhQeKC5/EEAeGhTqhgg/izwfy/qHuc67DNalxBpkm45cqWsXsLKwRBnAyCP6/J2z2+CVXGo5hdX/Ov3E/mONJu/EtLrtPDCD1FxK8+4GqcsU4BuQTMx8EI/2pmBUilc5HF4ftjKkACHj1Q5yWCo2w+wpfVQmajXrxbb81a54R05Z2TzAgJoFA3UBJ7S9dpNlrJu1PobV4e6kYF8iqqaagDFmBbItpmtAgKZXF1OA+crXXte4ysAZgZ2FWwS7wCQHkO6BwwfJJQR0W+DU9QtuTzxe4A5O1YDoLBbe+qcEcoV2FkYXz6xTVECcNQEIeMw7Bi4IJFmgG84LFOONUB//7hQxRlfDA9oirhu6dbTDHjNp1xnyecijkAVWUcWiA+mekKbq1qHmIxvqrPVEMQLDvrDvSKsnGUCcChoO6oV5wyW7JMk5+vOWxYjD7jtqq0LBFFCfH2bAGXYa2M1QWGGKDRZTvvB1AhlPfrliipM1BaUdYqZe+c0ccjwv2X88J+43eY1rLlqULnAF7R2y/hkJ8EPp7JtDWxZYgKC2wNEk7OvTT4uPmrdhSuX9TxbIbx5ZY66hnQDRAk5HJtF0P2Vtl6FqVNLcovKi0mL0bFBbJJDdns5tVEllVFR/Y1WP/IxecqBQGKxzrhwAsSCSoY93XCxBkTZbzHR+w54/O6BwBMZI/v44LP6xXuys7bR9L5dOdq5gWXpg+iW+bY2sOXQK4YzequuAB4QxmKthaPI4/9b0k3e8F6MUfSNSAct5b1EGs/d0ToCi4xboIjTZM5xQ2AVasZGCAYxaAU7b8LAXhlSN6q7nfrJ39JDgCaRKqhkp8sask892pXAaMDFuPoI0nnerZA21aTJG3VmV7MCS9FVchntpouTAaqCcPgqnS+KGDV+FIZ8ZFAFZAdX3Ta0AP2ZVVX1cZSTDZ3rEDfPyrsnsznZO/TA8wu5p5Mt2Xm8AM+OV1BlfDR9IAKwrEMVvEm004+lQFzSSjC2MVsIjmZe5Bi0t7V6vuasw+UCE11Eb4HQ21f5abi5M0AqOFGrNqPG03Qkx2C4zTaHNa/J7YxH1W61DiykYLHCNujWleSNlrQ5eXBAgaDZwI9frm9440OtmUN2N/mvlHPY4QM5p4jczTQUXAB+yiWTLLN8fCQMLxiQxUykJ8XYJ+34O3yXsucoCNhTF7dBkW+UZQdoKSglZFeMerE0IMRvSVz1zzWSsZNa4CI0d4TRUMUajUaDbJJlOmIDf3WkrUWiFZGHY0w/3I+4G7Z4U+//7/h/fiAV9X0RxsaOcAs9G7CjBfhETdksPhZA343v49ZkpPUDaafNeBV3uOj8R4fpXt8b73FfdnhW4/PsdTYrblsvkNYcjSSP2/+sE2se5mT0524q+4Q2Y1W3DJwt1+6NFz1LNdMBdjawKlgvJ0hV4wpFWT3vwSAw+3cof1tg2JuczMzk28b335aDaRFqc/rm7Ys/KbDxWj93Xp7VgPNYfXxQoJ5WzsNqFYHTxU2m8io3faYBmsnWrvRgskwmGD9+dWETjcjYyNIpk2tjE0MQYWgXwzbDNErMp4KpKOMN+UoZkXarzj9MaDTHOdgwMzRTEC6Q9ZxADGs1Ry5e6oTaefWPi4Dcg24en4CkWKMFWMsGLjgOi54Lx1xHWZMVAwgFVb8Tx9aZ+wmznisI+aacIgrrsKCc0iYQ8LNMCOSYJWAlQKG57MhkJuuspDf72ZxKZWB1UaBUm3E13y6+YI2mHOACiNe5S3pZiC+f0aeI8p39272rp2iQxdAt86RDt41bKhiMV9rfr4aHWsJOM9xGyOoIaND2kxWWlKzflRsHPkl1hsdbCGElOyDirBzXbGpRXnLti1K3j4uDM4Ezkb9aWIUnFzovkHwPauplfpGj6DGj420tSQcpdbcgDbYvv1JB104GrlxuPrJV0cmezDv64cEAFXaUISMLjbRQAwjZwQSVBACFHtacKAVey54kIRZEx7qDlkD3o/3CBfoQQCYOGPkjAq2ihYbqOnyPZgE2o/iHPpndtGA1tK6XClUpCA4r6lzCru7h1fVTVWG/D0CDhT1tnQt3Oka7PD9VkXXJobBAnaAi6nNcE8OLuX4Xktc362f9CXYcAQXXZoWHDuSvV0Yjq9oSXSf4TYQjpL7Mzc8QKuksIlbtD2BmuwpNa8RANhEKdjBOpVQJCCo0VyYLeimfd5wEHxBHfSknGD0OBUFs92rawkILIhBLdA5GlmEMA25i83EC3BU4tpntYns/x8OD/ZyZGyGgauDovxtQDGFjF3I+GLdI7JgHPPWTtenn7e76bTHL/nz9JoLj6/WVs+rUaHGMXeQrMC7ho2s7DKyl+e6yVr2CrcQJJi6F0VgXYJrX/sLKoAAr679mvDrgqcCrW9BsOWhYnSrtlWsXUAVW1t3sMyyvBrsoAbTI6Zs/18+qB19jCgGiuK2ebsVUw2oOeB4HgEAcawQt9Aib0Osg/sltpZTu9mC9HaUDkaSj84BFaFuBQX4BeLtJZ6KgbQek/k6ks064lhRK+Gz+wN+9v3P8c3rl5g4Y5GEhzohkOA6GIr4QRISCX4q3vUK8nfz+3hZr/rv3oQZqwZ8N7+PRBV/8urb/SYqLjn3f37+bQDAJ8s1HvOI7+ZbEFnlWUrAuqaexbf2+bjLKDkgn63yvNot3d5riBUxZAyxdPlGEUYMJjUnjwn1Goi7pW8Gp2UAs1GHVAn3p8laxd5iG2NFIEVJtdvytUSmGRvUyn0uzmdGmAn5WQWmCj0HaH5X2r5Ni04B62JBbHi2XLR97bpprUPemdiEHhz4uG7BTYSRM55IKxLB0PJRsD8sPZjUvAVhABvaPrkQs4ve6+B0lpUR7gM4k2FDknR3snAovWjo1MZKgATrjvGGqG1ykvOSMI4ZYyqY19Tv7xgEZ0cLhyB9jCTKONWhI4of64R8oVS3Z5vHHuKCVSK+N98ab9crDFFGJBO4mFJBqYw5R39No/EBwLKYDy/tff5aCFrDRhNSgKN2Bb/LdTmXTkPB+tXZebfYQJAP1mI+37Dx8oNlRyrWqk+vGDIwZIgoz7L5jhdDGtNoXTuaTU8ZEzoPuDbBEuAHCokftd7oYNvQqD37Ye2zF2p2SCx9LtrktpRhv5d0y1K9im0Bst1A1ABTsrUOGNZ+7vyqsXawTa9qRaFqbdRLWcfWEm4zY8q0tT0aKq7du+17n7E0JabWvo3NygqEkwyYOPc2cgUhAZhIMCtj0YBXdY8vygECq1SrMmZJONUR+7DgRThj9uq3eVQ+jycAwKu8x+ykdxMVrz27lo7ovDgXXqVT2MBPzQs3OhrSHtvmOeRJD4BevXOvILYLu3EdzV7wch68/U47fxsN4LKE8G/Jbh69OD/v1luy2CtZwC3Y+KlQQa9Am9AFoar2CqypnlUJ9jtsyeJWPdk9WhxRb+1j9P2mmxYkBURtg6/W2VFP2kk2e0qUViQ0pkSrsrHNm/t+gV6VN2czox95+9arTOZtLnn5L2D30yLxf2fv30JlXfO7fvTznN73rapxmnOuuU6dle5ODBo8sreQHXBrJPGQiCiIIHqhW0kQ9EK9UAIqGARFvBBFyI1ERL2UXLghYBT0YmeHKP/soH/NTjrppE/rOOc4VdV7eA774vd7nrfGWt3Jane606vXfGCuNecYNapqVNX7/J7f9/c90NvIkr1YNdaTQhH5z1LEDxloRRoiuViiXtTWFDotrPWarl1uOukQjVOWsR4gSjKtsJUMqbi1uKb1cAMC92eFlGXfNW0/bmqDU5RRV1HCanHlgamNSYJEluqlX1UshQZpG+Q9TYtd89B/nfWRLrahT1gjxQbAbSKpyKnVHg3l0uBCIV/MIiQ/COzARmamVrsxCmQVO5dO34SiF0y/QgS10KGsxbhIlm7oRWaS9spKK8icJxq4EIlKxjWoWQw2HGa22NGSukg4mxuhol4EeSP6W2czyYoVW99Ftv3KFpRMSss78xkXfuRT4V06MmPxBLOws4a3lp4vxEd8ZnyZ67jl9X4Nj79PA1+cLnm9v+G8e4d97rlPAy93t807ecpBISUhZTmXCF1iTpGlc+zHjhgdvRpyHw+9GIVczPiQhLGsXaqzhd4lyRAtpl0oVYoRnhyYZ8/+fmC7mzgbJmbdxCrMdzZM+n4Uos5yj2Mgzp7d+UjnF27nrV6ApUmvjM+wKWTrKEGMMVa48Ov0oX2xviFW2SbQbOQ2ijDVElGNKIx0hqARkkbnrsr4jaOHxeAuJ7ouCXs+m2bVam0Gzcr1QRCxaoJQJSf92STB9bcdLNIB15zc1BdyR7MYtLOhWEO2vh1m8Rk75HbId50y/ydPXvQw0Ce2amU4Lv5BUa1sYBD0zNmMN5mlWK6XTTsoT9mzFCfESSNyoGfzjp9/9pSXtge+8+pNona2t8ugxCl5Ha6GI0ty3NqemBxTdIxjIE6+MYfrATqqK5+EAWR8F4mzp4wOhojz8ruVbHBDhGKYR5HhPDAnqWTTXZIgg0HQgOlWEEoTMgyJRe16jS3ttSuLHGyyheIz7kL2tRQdziecK1AD5fcd7ubUfeErr490sa2GBzmfZBTW1B3tRlMyQogpYDZx7XD0+w8CgE86nLJYIViFk5lgWeUla37kCYywKEzksxRud9rpIScsdF83mpfZrXPaxljU8GhjS/vAyu8rbkoX3cRZmDhzE+dupLcLT7t7zt1Ih2wSc3EciqfLM7d54C4PbJ1kVr7k7wgmNZnP6/0Nj71YNToksWNrZwYzc8g9Y/ENQtoEid2rrGF7crHW363OUv0mflDfVt87Vus2yZl0YufoEtkncrINBahr1kQTu35JxPM2SyLQicmF8wmT11DqfBqH6AuFmgSlRbd7YWrxsVoZIcNgWwxbybSuqMXmVS7B4lqKVHWEMl5mtNVG0IV8YpJQ2gEx1xQgl1skpHxWacTBpHsGWeSHld9RUKgZea71uddZZLVyXE0gaASe2n5ViHyePWn0+EFYztGsnIf2shSxb+xMprcJp5QwmdkWgkk4jfHcuJmrzch5NwIS1Vd/fkyBzkqjUm1WnSlEBG2ytuC7JKqEqIUTmpKEWQ42dtDnlkx77VZpkPJctAN+gE7Vjt+uX297iRVoOicQe11llOtrV4JYdhZb1NUri7Tx6MnekULCOkEzGiHrQ6yPdLHN2YiDVBatJ8iJNLtCcUpuWhzl6MAXzp/sidE1tmyeHa5agDmnF5nOUEYnuq/NIraE3cJ+7EScrni9PfE8Ldng9hLHx1BEQ1uUBKAEHTgpzK6AzUL5D0prj8pK7rRI2NJcbkCK8RAi37K75qX+nsd+zyvhmp2dmoY26Kl0zIHFOPal4510wXXa8lq4ZrALn/DPAfhf02ucuyO/tf8iC4597mUe49b7ezdecBO37KNobS+7I/dLz/WyaRfqECLFC0t5SfJ6F1cI5yPOfvkiVtnFTs0mllk+irVrrWs+gWjGWTN7VQKUsyU4EceXfsZ712Dl7TA/eKxm5VYQyUAolNtOWKZPZoJfb/9ifQxWtC0YPmXXbPraYb0WOGXP532QjXeIuCA6zFIge/kMe5s5242kYjgcpHuqhvh5sdhe4iKrN3L9VFfDFbdJqt+V+a0cyBEoexsxVuDjsljMwVGCpli5mqil3shagEyFPnX2vMye/KxneMcxvmaxj3JDilq8pT7nMQa6TsZIvY2ajS2B8IOVLu+QOx6FA7/n0ecbvOzIBFs4xI7baeCiH9uoy5pC7yXcIEZL10V6n3jvvTPQrtXY0uSPJgn31DndR6Psj1l/Z6guU2Y9GJ069qk5UM0QTlW+Y2SP73rllVT9cxG7S+sKRc2OZK8QdGM5BvwzL8XVe+Llgu/B7hYSH4OIvVLg/k5p9raQDh5zdPLB7E+cRkLRU6jAlT4kliwQUPYGW+Py2khCiVbug4O8WhRLNhj1/pyOgbw4zEZOOqZKd5KRr6fy8OdPZhUPTl36xtcCLqdAOeE5K65I1d9UCu0NILPXJ+4eR2EsjoShM0lis0ogmCjyHzeyNRPBRBJW5rtWDDHejFf8yvwSj92e14MU47u84d3ljPvUc9WJ9+lbx3MOS8dhDhIOYPMDWYExMgs36rrVZtRF6PWVjXjqPJWzIc2S5HHv+qZZnKbAmA1nu5HOp2aoUTv9Gh4dkxy4qm6XbNvzqqzkyhIvWcTx1hZiJ9o+kiF+yLnLi/VNsqq9XzQr6Qlagcs1CvOECFM7qmq/KNCnFuUiWvC65xTsamXarnFh0OZoGhejwtTAGkLQRKlS+FsUXBWQfpnVinTQ69GeFCDUiKPLTE/AbGMz4wAZ+xhT6IeldabVfvGQO1zOTFmUCV4zbSV4wHGfenob2biFuzhwTEFiPjXvtqoVrCkEtX+UzF39nSuqVNE7ddEzammZs4THpE1SKZXOrFWOYyzamNA0tGvSkqJuphBnDwXckBoLOlXCWxCJEKrVtVorytGtnkRdIl7YlXtT5UT3AW4/HCr20S622VDuOylwW3GQ6p5b5scZNImnJIvVth/kA951USKzZiu30zeu6AynnaT8CmO24oBeoNFitnqhHbxcZENq+H8BdSdCNvRTY/NKeqgXRVEYqOo+T7rlGkRgTaHzSQTnJvHI73nV37DPPRnLE3vAmsJ1FsLCYBbGErhOOzG08Pc8sXsGE5mRXMqdnRnszM7IhfO58TFPz+749vAOn1mecp22vDOfM2XHtwzXWDYcY2A/B8Yx4P3qveqswLvOFLVTLI1xmJSklLRLAIF/8wksX0ZH8YbRhgYLL5OXOcxuZPCxzW7rTNsbuZ+Uq+EATdawUfOPlN1KSMv1MCPh0ilaihFiyoN5z4v1zb+qCiFZ3EEJjw5xd7ISYlKUe1Ed4rA8IBVJ+LkWiZO7LkkkKNXApRbRnK0EyWvsZ7EFtnEtPEaKTy5yCFznmRVG1nUy7pKfK5rPaxqaVtNqrCon8uKwm4g7z4Qu4p34Jadqzm+h62OTFmZMm8GmYng+b5k1CL5zkU9un7VoPcLIk7Dn7XTOW8dz3tg958KPfOF4JQxlPax0Tq7JvFgqE8a5jKksX8D0SQ44VsZpOasD3WbNxC1RkQhbMCY3t6dSEsvsiYtrqWMtlu9O0IZuJ2qNGDUHd7GULuK7KOYe0eK6BBRi8u119iGRLhVdSPL+5WTwtw6uPwYEKQBzOVNmBzeB4gvTq1Htt4p8sPVkmbNhf7ORtJouNv/icqKPJUOZxTLRKmSzTEKCqsHpOgZp1H9rJB8V5GtlseS7IP7MQ2oEnJXVLHCFOSoUNKQ2d8HrRWZUUP+sI4bCfOFJWewP7+eefew55K51rZ3OU3IxfHF5xGAXXnU3WDKOzJXbc2WPjMVznTd8IT4CxCMZ4Dpv2NqJ33v2y3wiPCeYLCzl3PGduy8x5sAvH19iHzt2QXMxfVIzCkOn0puksNRmO1MK3Ow3BJ84GyY6n8h9xNpMzJags9yDkqk2Lx2azjaExG6YGTqZDzsrySGNoQytm56jZzx29MPCtl8aWatqcQ9jxzwGzHsdeZNxF7O4cKksIkGz4nuxPkarQq29hGmg8zmiaRKbBicr9IihJc4sCDGy6+LaJVFdzWjBBS0oIzpSRO43ZMzRCfQ71AO8XZ+XFslKgkjxRBnhM6XTg+OdJ28SZlsaUlaN+KuutxZ7V015dNXDqTGF4XLC2tyStbY6Utmnjk7zrd/YPF+d68g8Cnvpdotl42acyezczFV35MKPnLmJx92BYwps/UwuGlI/OI6Xq72h7eQ57Q+9SAC7BCTyIJD6fAgPLCuNkS60mubkbEhhJazW18no73f6M0DzN0jaXReNA7XVsarO7U2BQQJP6uvkfKJkR1HU2LpCfBTJ3cdAZwvQbxbGZHFHS7yMdJc1QBiSMoDlCwgs4NUtJmvhLKyQbjGYWWcGGWxUardzxJRWEpZ2oxQ5wdqwwghpBnu05LMk7NcKa+iqcLGdxAO5DfYru1DhpZyNnLhDaY4rcXHMyXFMgSkHUrEEG5tV44jIe7Zl4lV3g1Mx+s7MXNmZL6SOfel4a7kkmMRv775IwvC59Jitmfht/ZfoyDgKGWE5f7J/m6V4fu7uE8zJtZQPZzJjDIzRE5TFSHJgM5tuYY6Ovc6uDDJnTUXYyAKLqyNVEsr+o7MD4+K5u9/gXWbXzZQgr9sYPYt6HJ8uY0TvFidHPyz0PnKXe3Jy7bYxOsrkCAfD4k1LQ6mzsoJoAh+Yzr9Y3/xLR0pZi5fxsumm+3Bi5VfnoqLPLFUbX4lMXcTbrN3bKjWr0pBTWWJRP2UpmGv6V5MPahwfxkCXVA/6sBBb1egXX2AyomQIJ4x6o8U2gXV63wWMEyQnZ9Ni42AlDJ1vR6wpLEl8kzsn89klOzobCSbxJOzZuglHwRo5xAeTuPCdKBWUMHUeLFuN5tu4GW9T65Cn5DkLE4+2R6bkmKNjCOJgd78fyMkQutxco6YxkPdOCGNV6FEbF4TEWpGxnCxplkxze0KUrMucEDUb0gUaWlO/gY4B5DWrLoJ1tu1cJp7WFFNwZwvGfLiZ7W/4ef5Tn/oUxpgP/Pkrf+WvAPA93/M9H/jeX/7Lf/l/67HSogzWzUJ8smA2wmJtWtfFYma74vgq/o7vDjBZyiCQUY4G12WxUNsm8jaTOmUKn+g8q/+m0flumpX8UB2NZoUkfZGT67s95ejFSengKXv/0GezPJwl1lCEWtTjywv56SyJQ6wXR+8id2ngi8ujZsv4hXjBm/GShCVj2ZeOwSx8e3iHczszF8s78YIvLI81DHpiayPXecP/89nv5v+cPsETO2FN4S53vO6f853DF/hUeJdPhXf4v139Ev+Xq8/xye0zLrojY5RPf82nBdHRxeTE8s1LVx8Xx93Yk7Jh188tcaRziV03c3Y+cn52ZBsWufBUcrEkcbwZ/MLLu3s+cXHLRiP7rq933NwPkos7zJw/OnC+Gel95GIn92eMOOWEkHC7hfmlCJcLXRCZ1mHfs4yeNDntRF6wkX+z19dz7whvB5Fx+NQ6Se+ToFGbhD1bZCNtHaYUWnPwGFfYPj7gfW5hG9VOMCUxdampUynaxvEAIefZLpHPI/kiivmEWgviC6ZLzb0uTY589Phhod/NEhQQpBCbbSK/MgnUehcEUlWpoDGFdBfI96EheM4J3NoPYm8bo+hWvU90un/dHwYOc2DjFs7DyEv9PVfhyJmXBmbKQWM4bTO2eLm7ZWtnpiKa3CdhL0oHvY0jc+GP7NyEt4nOrpm6OVs6l9iGGedl1BeCQNzGCEfFX8yEQVQNKTriqHF/PuPPFtw2skxiYtNtF3xIraOnCBcjRidjRAP7ZxtGlf+UxWLuPOkuMN31gmpUPggCHVubibNjuhkYv3BGuelkj9c/NUP4w6zf8M72Z37mZ0hp1R399//+3/lDf+gP8af/9J9uX/vBH/xBfuRHfqT9e7vd/m89Vk4Wa+Qiib2eQmAtZjobbSdKK8XWjpa8yTJj1dsbkzE2kzXTUGjj+u16eqonIiVKVPN9iXZC4KcikKRZZO5Lh/5bT5O9/l/lSSt0ob9UnbeYgh+ibAYn8h8Qc/GlOMayvn13ecNYgkp3sna9iXO7MKupxVgCS3H0SooCWIrnZhmYcqA3cJcNYwkMduGCkZ2JLGQeu/sWTnC9bBshxJ94JlcyhLeZqKfTUsTq0rtE0NtWOMqawqZbVBaQVcOb2+9Ybzu4RQ3M5SLMUU6wzhSsFvveiW1cLf6TQkpOYaC8sS1UIp92KNAQhRfrN3d9PfcOE2lM+CrJszojxa3m91VLD8h1mQBb2PYLxzkQo2nGK/W6rXKzlGzjJciDrjPYoglh1gpXpPox13GT3J/88T4TfGpmFCBFu+sjY+owR0PplWVfDTPy+picXG/GFBbkUFBNYayOgGrX602m1442GOlaswyZxdb1xJ5xMIskcCFWr/Zkel33g2BTez71Oq7fr6YX1bDC6G2y7qs199boCK5oWIxh7dbn2YEeHGJ0D3732hwZmzHFyQzeFkwnCJtRrkxp6QU0dNFa8cKuBkR2NuS+PKya2bQIxF9v/YYX26dPnz749z/8h/+Qb//2b+cP/IE/0L623W559dVX//9+LLP3FGS+YKxswq2wthsBszAL6wzVyPy7/Zx538Uiukv9muZDLsqQpUi8kjFFBuq6cjK4Gy9uJH0h75KalasG9bbHJEPcJTmN7vS51TnxYijKuMtFPTv1vp0RWzWnc9Jn047XBjlRvpfOuE5bfml6GWcyv2PzuZbmszORc2v4XPS8mS4A2NmJb+veZmdmDtmztRN/4unPNjnQe3nLZ+ZX+F3953jqjszFMhbPlxaZ874cbhlz4J3hrP3u19OGMUpYQc3D7Fxis53a5uCsxHpN0TcjdG8zl/3YIJ/eRx7vDizq5TotnlvT4y8yWz/jVGbUP72j85GLfuQYA/fRtwt74xd6TNPw1g0mRUcuhrv9IIW2Uv71YsnjR36i8pFfX8+9I336yNBl5uhZZt+QjTw6sefrTgpART56SFFsQnsvc7rZunYI7LQgVjez6t7U5q/AMCyiJT8ZiZwmXTUpkMtEL9reXru9mCzJaHCJfq7DEEm++iaX1o2Z7SplczbTh9gO7PXv1U3quARygbPdyPkgUZ3H1LGPPVfhAI5mw0iGYCNLEVLQUhxbO/HY38vvUiyH3LMUp7avjj6L+iFrA3DVHTnGh7F0QycZsjXIPiVRFNQAGGcLh7seMzkhrnYJ5zLOgdlJTKd3YrEbCzhFKmIUglYICdMlikoCc7bkLpF3tjnzVfSh5hLL+yHyTzYL5sn6fKtiYr7xIl36EOtrSguZ55l//a//NX/xL/5FzImj9L/5N/+Gl156id/xO34HP/zDP8zhcPg172eaJm5vbx/8AbDzep91RgIrNCtMGu0q6+nDqghZRdGVqp+TaZCPhBjklsSBWSHcdurUE+OpeL2SKmom7jqPBZMeFvlm3Xa6olxI5X2whMwVtcMuq5XaIXfsc89t3jAVcZOqhVbdPEmlMBbPmAVWvnIHntgj51YsHTsSb4T3OLcjU5GLxa28xwcd8VJcm9UMfqFzkc5pEEQxBO10Qan+LqnHtCIA9f0phjk5xuhbQayvb3CpaWXr+xmzZU4yrxZCVmyP1VlJKgkutU3PUgOwwZ/YRcqDP2Qmv1jfmOtrvXd06gx3yhYWYoxcv6V+z6xa+g8YJ1Bdl6QYeJfxLrXPe1PqnPyMMevtTjXopztBNbtwTiI+4ZS9v0KdWVE2q/rSwtqR9UH8x2tW9Ok1ICHv6+9c5Xje5Q/o4tNJibAU5YiI2UXdC4JJqvGXFDGrQSi5GGEzY9+HfK263vr1+jo360U95NTvOatdu74P5uT9cRrs0n7HshbDlSRFK8hye/m/86mpKmqWrq2ysLIil95nhm4hhNgez5i1PnyY9TU9zv/4j/8419fX/IW/8Bfa1/7sn/2zfPKTn+T111/n537u5/hbf+tv8fM///P8u3/3777i/fyDf/AP+Ht/7+994Ovh+eqfa2zGGRE4p0ngghou7N/qZMZaO8cnCzUkuixK7V8sJPBHybYsr0wPOt6SaQkeBSjZNj1WnDU66vGyBhEsBg4deRfBFfwMNhoRUYMK6JF0DyvaMnvvsIsjvVJZcPJmL8kxRy9ByIMkbbw5XvBs3vLacMtgF4GNXWwSoEMO3OWOfcm8l87Y547f3n+Rx3bmFdeRMfx8hq1d+K1u4p1c+Gy8pDOJ7+jfxJrMe7nni/ER12nbTrLvxnOm7NmpGxXAO+aMmCzbzUznEtfjhlwMm27hfuyZjoHgJUUkOgGarm935GQZtFBWpnFnE8lmgstswsLGL6RseR63XN8KfM35AaNpT5f9kdd3N0zJi1XcPDBl1yDmYDPQcbeIXq/rF8bYtShFQBCI8uEYhS/W12d9rfcOY8QkJWerRElDiga/iZSN3CYuTkxlTg7xRGGyHpc1GN5ZPegBsxqoGAMhiN1BTk7kLLqduGrjWGBeRKqSjh7jM76TsJFSxPjBW+m+S3RqiGHw2yhb1uSbNWTlqmRvsFaJiAXG2VFcpocWj1nh2yqlC37N7K4hBNZkervCydWp7sodCCayFC8jqxNIORXhixxyx30a2thpyp6YhdhZ15wc0xTYBwlBqK/luO8wrnBxfpSs3egEnfKJfrMwq/zKWCnMtQOuhTmpt0FJlqiKA0lM0vdn8StErMQqEKmh5F4bIaiZIuxmUwght8NAs9vUg4Md0jdG6s+/+Bf/gu///u/n9ddfb1/7oR/6ofb33/k7fyevvfYa3/u938tnPvMZvv3bv/3L3s8P//AP8zf+xt9o/769veWNN94gb07JSwob2kzxwhJu5tZBo/cUMjamrJmzIKfZ983t6qm0zUja/HbNq7UhtRmJ0MtVGyuqctHs6Vy2BMSwX2e0df7T0n6MPMdSb18U3kTkNTE6ytETzyxeY63CCSvwzI2c27E9f7FjlNnuzk44k7myM+eqmUkUHIVAxhqDa3PehY7UutnbNLTs2xpckLCrjyxSIHstfrULbTNdJ76kzmYOi7hQGWQOVdzaicJq61ZlO9aUZhMJMqMpxRDU1rGzscV5pWI4qMsVwBQ9uUA3TJIyosQTo3OzFX3Qz8lptOGL9Zu+vtZ7R1wscd7IDLXKQlwW84dsVgbwRuHlSozsZKOfo5c4Ou0EU7ZMi1f524rKZE2bqiYap653KatVZDKtta3ywqxGK8UZcbw76f6MzZSs+5dR/geqYkiiYU3BiA/xMeBCovNRdL7FMM62dWzGFHzJknWQLIt3WozlPmt3Oio5ajALi9Fr0kBgDUMZc+AuDxxSLw52xRGL4xgDqRi8TczZc4hdM6ip4QjvRw4fwPGnt2kdOc11zocIaHa5FQOjJrmaHeCY7VpgK1BSE5lytsSFZkAyz67JL40t5FzImWZ8I1GdrqEidVT4662vWbH9lV/5FX7yJ3/y1zx1AnzXd30XAL/4i7/4FS+Yvu/p+/4DX59fWRiUiJAW0Wh1XWIxUNRfuGRLvEhCOGqnnMKcgnSgQTxOG7V/VJ0c+kGYLTYInJOik3nfvZcs3Cc6ky20oOZSpOs16vUp3p+WeKZevKaIscJswKnEoELVIZP1k5CzIet8IibHPHnCc8d03tHZxFU4cuGPPApiVPF6eM7OTiSMeBubyFQcC46nbs+5ibziOra24z6PLCXTm0JnpMVOGBYcAwuDiXxhkY72kHsShkdedHVfmi+ZsnxsFnWa2YWJ3kditizZsZ86SjFs+5lNiDzd7bmZBt6937HtZwYfeelMvJh7haG9Fb/VziW8ES3ve+OO+7lj8HLCf/Xyrr33G79wGUZ2Xjyi72PHIXbNReru0FOK4WKY2IYFru6Zo2Ocg7A/u9ys7pzPlPiCjfyNsr4ue8e+Y/dWR9wV4qszrhMLxrg4mdsedWMdFtl4Fycs5KsjKVnGY8dmO9GrOURMlpubLRTot0L6K0Wkg+beU3YRu6kzRAknyMmR7rTbayEFayZ01e6Wm072jotFiIFeGbfalRWFnQsQJ9/2unl2lGc9y5AY1SoyRUfcB1gM9kJY08ElwHCcOpwtmmFtWQBfnGjui3SgB9druthMbxcGt8penqUdb06XLMXJzxfLnD2/ev+IYBO/5fxd3p4C7xx2TIsXF7dkGY1vblvWSwe66Kw1RYdyS6XjzxIQQLakW33tLiDn1KD3YSuhLjlZ0o3HzIYpGUzI0ukaKaApOjkIzVZGjRcLNmSWg77e6kq1gDRYkxMUrEuko4doCJcT7jdbZ/tjP/ZjvPzyy/yxP/bHfs3b/ezP/iwAr7322lf/IArJzpPHvtuxXMYH9meNlaxdS4oW6wzGqI2gnoKsr9CzgV4CApxCBjWRousiU5a8VsnApQUFFMdDaAIxrqisWRsS2dvVNYoirgwZzGiFjBWyzHFrI1fABHlufYgsw8LxUeB8N9I78S299Mc2Jzm3RzqTuMsDg1l47EYCmYHIuRKlMpn7PPJWiszFMigE9G5KHHIgkFiK47ps2KtpRm/Fdu1ZPGMqkvxxvWx463DRuktrCp2JzKknF5mpAo2tbI0m/XQLu24WFywtrtW8fL/0ZAzHGOidwZqFMXr2U8dZN3MeRqJC2TFLVuYxhVVobwpbPzMqVCXetaadoFO2zNEzjZ2OBCrKoWjF+2K7XqzfvPV12TsMpKGI+uCEjFhlfTWYos7vKlxbZ7HWCRmwzhNBiVDFNK/h1hn1uUVovj/IpPE21vS6RsQ0ylDOg0R4VtZzO/RPVljIIbafKZPAY3MfpfvtsgRvnDKZu0Rxtt3XpJD4sjjm4FiyIxlDLivsu7UzwSYGuzxAzZbiSEgK0KKH8FxsK9hJ2c3eSizfnDzjHDgceuLBE7dOJD4+CcEpCIw+7ruWx1tXTf+xm3jCHNZULz2kWGV7p2RbiEOxZvWQRp28ZnlvbJfIGUqx7WfFh8Firz2lK9gnEXwhZXUXU/cqvI4I5g9XRr8mxTbnzI/92I/x5//8n8f79SE+85nP8G//7b/lB37gB3jy5Ak/93M/x1//63+d3//7fz+/63f9rq/+gaKeBA+esy9ZDsaTzub2Qa6QoqkpPJMjhyxBxAYIErPnXCbdBOxsyRdRbg8yiHfCTtt0i0RhJfkAlywMW2PXi03eTLmQ8ugxk4WLBRcS2TsNj1bc3xbsbHFHQyRTPPJGmtLE1U476m1YhIjhMq+c34sOzo1cOiGHBJO4UAj5C/ER5/YoxVbTOc6t4dIO3OeJfcl8Nl4C8Du7W8ZS+JVFmMqDXTjknuvcc5c3HHLH6+GaVAy/sLzClOXiu563fOHmkrNh4mo4ctGNdDZxNw/kYjjv5/W1rwxIF3FD5lF/YOtneW76vSk7xhTI2XFY5DE6GznOgeOhp7+65lF3ZFHpwZiEfXyIXWNJepO5DCuMvukWYhJIu8qPpsmTDl5iyVQmURGMD6uVe7G+tuvrtXcYW4hblfidat91zMCQ22GsknBMK7Yyx6vkuwrv1iJbIduq78x9Ej0tyLXfpBBFbCM5GXnpbLc+rrUZu1OSlELHUmgd7mBJXmDMCmvao8MkiBuZ5zKI9vY06zkMwvBdZk+KlokgM+vZsnQCI885yDVZpGheDkcu3ZH+JIgAYJ97EpZJYeN6TVfpHrDG9mXHmDzHKRDvAv7aE6MlDY6zqwN9kHHTceqIN4HcFfyjsb3uZXTYe0f2UiQ5KcRrBGem85FFU5rMJrWDCygpa7GiZNkkhp0QQzPiCCXpYYW0wPCuJW4L5uXcyFPNEVC10XmxClX/+utrUmx/8id/kl/91V/lL/7Fv/jg613X8ZM/+ZP8k3/yT9jv97zxxhv8qT/1p/jbf/tv/+890EY6VNMn5isvkpsTGv37zSOI4jVcOrU/M5Bn4dUxZPIm4fskNP+ieP7kyCEx+MgdUKLVGR8Nkq6m3sviZEaTDKZP0Cc5mRWz/rFFnpApAodg18B7JWmVoEHx75sJLYtjip4peQ6p484OPPV3bO3EWGSmUuHgpVgGkzi3BYdlKYnPJcuzdMY+9+qdXLjOns8uL3FuR564e/a55zptObdHzu1RbRsFhluK5WYRf2SrXWvtXK3JbPxCKNLt1qJYL77gEr2JdDY9KLR7LZhbPzNnsWSM2fJ82rLpFrqrxFkQQfwUPXN2PJ+2BJt43B84xI439xc8HvY86o7E7FiSY/CRrEESMVvGxeNcoewWJbiZxmBPs8JJL9Zv+vp67R0lG/JFlFmqbsTz5MmzE9JktW/UZW0hJUOcPdaVZmSTC2yCEPE2vXAH6h606WcOpSPNrmlGsxrjxOWhE1HLXVYjfHNCBKrMXGtTk7DhM+msyP+10y0aNmCKNBbFFWyfdO4oz6ukNW83772EpeziCdJTiNW0wguidOFHelNVB7b9P+uh4SZteHO65D71zHktKUt2xCKz6bEYns8bpuSFZX2+kPqMC7LHzbMXm1UvCoayyZhuTVdKyWK6TN4azJ2H4mGT1AFKVQuLRHAWp+iD6mRbXrUykrO1zUs6Lm5loRdVpCiqePgW6Wg39b1B7HQlBcqJr7IrD4Msfo31NSm2f/gP/2FacsXJeuONN/jP//k//4Y9ju8SxkiKy3JeBDKoA/CTQbr8hWbDtuYaipcxyeB2UWngUjhjlHxL6Z5FA2r0ZGNDvRhK8xSN2ZJTkBNkNlj9oOQqQ2o4lVq4OclMzIXW7RINdhHdfP2wNLu3ovOLLLOQKXsOqSdoxF4ttgLdyG22JrG1qocj8Wa84J10IdIgkxmL4ZAD78RzkrNcuT1jEZJDnQF/dn7KIXckZD57v/QsyTXxudfuGcSg3BfDZRjJGG7mgVwssQjs27mI1xB6a/JJl2qbH2tnPUe1gTzvJzZeCFAgSMWcPPu5E6ayW3g2bXlvv6V3kctuJCqEFVxqP1NAIabMsEmS61nkwsQIjEh80dl+I6yv195BgbBdqCYyWe1QSzRtPCV7BY1IFJfQ0DFM0fSawkY7sqET5vy4eJyR8c8cPTMCOwefWLQDrfsOvup4gVwomMb/qKhQk5lwsne5glGou0Xz6f2VUuTznA1uqzPVosSvJKYU2YKZLHY2pM62oJTK6hXoN3HmdFxlY2MeJ4w6RGUSlkPqeWc+Y86eOTnlXWRND5Lrn8K6dxgYNjNmu8Lb0xiIIBIcg0QZetlblyQmHMZnSg/+2mFnmHoDrPB+TqYxtiuRzGBXhz6kc01WWtmSpbjWoAmRVq6da3gynmitC8aIjMmUgpklwCJt8ior/XXWR1rJ328WghPj+nEjVmuhixrltkbVFWvI2vJjdD5r1llMOYEI5inIQagK0reRzSASFO/Tat+Gzk70dLosjngXqOHxOVqWYtQSLkucm55aQVmHrrSuFmROlL1C4Itl2g/MXebQzxymQLwPHLYdzhSW4qQIFvngvxkFCr5yh5ZrGwwMxnOTZ+6yOMc4Mp/wzwkmcciehOGN8AxrMtdpRyrKOCye6+T5+cOrXC+ihcjFMriFxTm8JnjEYsUbllVSUH1Qn09SBB/3B3oX6Wwk6mmXYjmmwGevH1OK4bWLW1K2HKNAV129yLIU4uQMt8vAlMQn2VnHPgmUtekEZl/y6t28V8ZjFcnXTUpkFaw6aRQS8h/c4F+sb95lu0To1Ft7kf3A+aKKgdQ2bN8INaYdzoxaHzrNmq68gUG5CrtuZk6O26MkcG3OR5ZFvMJzVOcy3eAlJk4/h5aGZlXpSY2TwxbOLo54fexxDKSbDros3Wv1TVbugQ0PYe/T5qOOO8s2kTqBVDGFPGTmsAbAV7l9lfAIaUoO9IfcEYpjMJHBLrw23HJMQc0wOsYkrOOUreRJZ8s4byX0AfE9jrOTuEtThJEN1FSv0EdBE4rheOjEkjLI7Ht5EuW5aTh8ijX8QZEqnZt7n7h78xx7tPB4xvoV6h+vZLbdmOK2NAS0BsP3/ULOlnGsxszy3KzLRFU0lG3C/GYTpL4eS4wTVJDcCdPMudwICPVDJsQCKxcSKFFJmcCmWoEJ+en0wy0D+kTnE95IlJw9gZYEWbDEKIXXRIUVnJCfMuC8fABMtYZrDHc5xbZQAwCHFP4ixd7MGk1XU0WSFLRUDLE4colkrFgupi3WZJ76WzqzWt4BzKWwV2tH8UVeGEziWucuV+7APvfsc0fGEowQpebiuV423M6b1nmeiuNzkTiuaNwDR5wlO+bsOC5ByVFRDc3FyDvpHChm2wLhp+TbfdbNq91/tsxG4PMprrer/swtuqtU+7fI3dJrJ+xYTshP1TNVZBNGNqETKPHF+ngsa1dbxWo8X7X6zQzhZB4ru3mRS9idzHBZuSH1cxtsanaNVs0ulqVCvbZBmpVk+cAU4aQw1rB4ipFOFjQjWmaSNeu6FWvExKb6CoPIYwoPr1vQPSkIk9nuxTs2dSeza8Q1qqJQjvXnkyb4ZGOa/v7cCV8iF8sdAicv2RFVbhSTaxaqcngRA59cUb4qYzo55IA6PS0WO8n+bXzBbBTS1tem/qxxqzlOJa+ZRUJfkpLa5L3PuD41hvGaSLO+NtYK6bIo8tVIa8Gs2mIjcLMzH4Niezx0PH16xNncLpDTzbTYKuFRBmA0EArhbGY5Bsy9b2QkCZuH4S1P9oX8bUe8nl47lZ5su4VlOzWXk0pKmPdStOzFTFmcsgRzs3WsqxQoBzX21EQgFoVwutyeS/M2rf8uRqK8riYxilh6NuoXfJ227HPPZ8cnnLmJ//v2/ysReUXclg5l5p205S5vJM/W3XBlI6ms85dze+S9dMb/Or7Oa90Nr4RrfmV+iefLjt4mnvR7zsPIPvb80t0TbseB+8PAtATufcdZPzfpj4j8M4cl8Pa7F2x2E0+GPUcTsEjh7W1iyqLPfe3qthXJYBNPhj1jCkxq/2hNYb/03MyWa+0UrjZyYb973OFtpverFZ0UZ+mIj0vg3S9dYkLm0ZM7YnIs0REnTzk48iCyL+sKhIcHlBfrm3uthBphvOZiSIuGUph1XirjB81dNWDM3ArtNPmWMFVJUdbmRhC82I4c58A4BYwBr65VTUevf6+OSGl2lNGRN5EwRNH6Rivcj251nfI2c7EbOfj1Mxuj8EUotL0wRUd+r6P0Gf9oBP0dnJd9LRdDcYX8VI3/Q+JsO7VDg1duRXWIqqqDVCzOnKs1Y8eYQ5vXLtnx2ZvH3B17npwdcDY369TdMDNHx7x4kRx1UeU8Fht0bj47rLV4LweU5Rhkhv3yiD0Zx5VsoMmz5GtpBrMteFuzeh1ll4hdZrOdsbZwPPQqz1QtdTYwqzfykLDK3M5Zc32zwPolQpkdSYlrRotvhbo/zPpIF9ucTXthrc0si2dZXDud1Q9zi1SyiJuTzzKiK2BqYUvmhAks998Cz7UYVEJQnQvUOYGkRQDhg8/x1DLsdDXD8PpvU1ahekY+BNWIQy9GEOH5IXYck6RzTDk0I3C5MDKBzIJV9q5h0a52MJGt1VMhOnvhoT1jPbVNmmfb6+3rbWqGbU4aVVgMS7YQfYOI6u1QUsacfEv8AB50wRu/tCJdC2a1W6zyoGMJLMkRk2ubQCyWKXqSSwy1E8A0mLodcio0ZIQVmayS4+qca9Xnv1gfo1UlNs0ooQa9o2QYRTpqOk4XxPrQ+5UpzMmccDGin7XFMNXPqX1oFdoCC1BYuoijk8EIKbPtPw3+oubuPji0I4/fh6jzTNHP5mgaZ6USsUw0EiHYuB+sTQl6sFD/gRBSY1iLNWNar3ssFHWMOrlYkvJH9rFnyk4JimIUkYvBQUOWJAPbtN9FPMv9CVNaOlmKEL9KFgYyW3n9l8W18Z4xpRHMir4X9XVztrAk4d0YJ0EPDYnQWS3lhEcjd6Kz3aKyTNtyiiv5rPqplyK1ojiBlU3+Mhv8l1kf6WILkigx4VkWz/hsIDzzLE8i7mwRByaV/GDAnS+NRWhDJm2ypEhEQ9F5wPTtKh+ZHXH0sBhuTCGe3TRIpFLmy1EYhSbXOWuQi7SXCydHgxHmA6BavX6Ra8hmsndttp6jiN/dZMibooEGCdsnMeEePfG9gevZ6QxE5DKX/sgjv+e3bt8UKzVE/zeQGIvjtgjz+MoeubQLwcC7KbTEoFws13nLYBZ+z+5XWIrnkHsOqSNmx6v9DQC/cnzCPnbtFJcWy3abeOX8jmfHLYepow8ikA8usTOF6eqAd4nracPjQbpjyeL1QmTSi6MmB03J8+5hx66bedQf9PmJVnaMXozTTRE4OTnujz3eJ2bv1Cc5coyBOYul5cUwMr8sANgcxTB+0y2MoSPpvAdOCCYv1sdm5cURq3Qwr1aKdabqfKZQWK4HsIXw8r1AkydyH5BxjzBpq8JBim5wifNhIvhE10mhSHEl5TUZz8GDL7hdwoVMPltkZmgk9av0K9lnjp4lrcQsawvTGFhGj70O+MmwXCZKUCmQEqZQIueSPfnoKZ0hudI+8y6UZghRZTobt7DzE1s3E0ziedyxFMelO5Iw3MQNSUdO18uWLxwuT4iNc0OfluTYH3usLey6PagmeJwD8xRI915Yvbr/4grFZ3IwRDXyWYAyLBI0M1v8NmJsZglS+H2fmrOf89L9T5NvQTHmxHKzOfotOlrS2FUyMKs3QpcwFqYpkCaHe7cTApWD7ISIa7aJPGSClQCcD7M+2sX2/QcK974M2soEVhFyM7aPkuRDtUmzIrspuWAHzaaN2h1ZGbavrFaR9rRZCohbFdDi9bRrLVrE5WIBytqh5uSE7Xy6LBSnJzWQ+YTS9K3NYrbhNfnGiVVhNQJ/4u7Z2okFSy6rBSLInLY3iQwciuE6b0gYdmZmXxxvxisGM3PhRsYcGHOgt2KcUeO1qm1bW2Y1rQhOTqw1RMBSmrbV6fdlpmqb4L2uzkZicdzPMmMdfMSbrCQN11CFej/NGN4I2cHb3NJWqqGFV4KJR1JDFnWOEuH8wgMDcT3hlvzhLpgX65tkldV+ry6ZwerBuUjnWdO3SlGzmpOZYC66t9TRle4Rc4ES0APiSvx50EnXzqrQmLGwknzEClBkPHIH5sHzlZkwGlaPHM7tyfVZgR2vBaw+bg2lr8jnScdbEbv3BxeAdLBLdtwgZMmqs8U+RKrez+lYYwFPEn3ayA/d82QWXueuxtK63aokSvV3d6sUiu6Drm/VQe40rrC+ng9vSEMOVANItdAVGZQevE6Z6a4IF2exwlrP0njxIRPDPtLFNqvmrGZGducz5WzGKCRUlFR0Cg3XgXs5ePytk+42FMK1isHPlhax5EPicifB5iCntBitGFbMlQxV8Gfy/dROt4WySFfMoK4mLglMjLyJMrstcvKsH/g+UboKIZUmH+qceA+P5wuXF3s+ffUer29ueCnc85K/49yNvBHeI5jEXe4IJrEzsQXLn9uFrSl8MfXc5YE34xUA39G9yaH0/Oz9t/J6f83v2vwqY+l4Fs947Pe8Ym54Fs8Yc2gFN+r8xXkR9XuTOQtiwVitF1O2jNFzuNlQLkZeeyrd8bGJ5E2Dg3sXuZkH3ro5ZztM/K6nX2IfO+6XXrrU5CRY3i/02lUL4UrycYNLbPzC3dzz7mHH482Bc3WSihpOPS2e8bbHbSK7XoKqY7f6nKIn5hfrY7QMYpXoC24TV4OTRNNhyxhKbi7OcFLwKqM1L1Y4F4NoWeOk3WTxRC/jpjr/TUlci+oB3fiVo0GGODt5DtV8oaySnxQFBYrHgLGFfliIi2M5BHGZ6xL5AuJ2Lfygh/5BQk2WWTTvdit8FSbXwuZBDpvT6PAuKx8kN1vWUyj5vWknUHGxQnh0CxnTbBu9zUzRE6MQs2TEJ7/TFL3MbGdPVnctu4ltzmxMIfTV5lb2x3Sl/z543Cbh+jXfdnM+qWbZ61iARigNysEo+cQC83RVFygdLaJSKIlQTThXGG96iJY8ZDm0hCwz9HuPjfK+lcmSp99kb+Svx3J9ZMkCE3r9cKd2Ej25ob7OabEr791KF1w6mQ/ErcVGyLeByfkHpyZxVPFCrlFGXbGnD6APoyeoklQUHwSinGffuuwyObnI1NWqEqRsyOTsNJxanmPtaJc6T7KSmbnzM1srf2rwc6Xnv5fOJGbP34kcQY3CpwK/NL/MO/GCoHT9Q+5JxbJzE8FI+EB1gknIpvE8bjmqxKYuqyQLgFmZx9UW0ZrSCnLYzmx6yaGtDOU5CYS89fODOD7vE0HZgofY8e5h1y7ASTvbRRNaOs0DrR2uZc2trSfreqJuJ231VV3UM5VoMb1uNl0WBsSL9fFZhhahWeecFVGiQL5XAobV2xTTZnjAKhsMmRwNOXrKXtm2Ww0o0ZnuUqQIV3kJoEXZNBekEq3OiXOzf5XHPEHTNPg8Rkm7eT+/pIWcGFRPW1p3V+e8VlUW2mw2q8rKtpWDsKT91MSfSpKSP2orm2kyv8rVENvUTCqGWVUDKVejCMPN4uTgMHpMn/Ahka1yKlRG9WU5LtFgFivOUerjDKceBPr7To4UchsLlKJdKvUAc/I+N2SLVg+KBlJ4rxF6p5plI0hjSfIDVbJZfKGkj0Gx3W7ntsl3Pkqma/QrRGP05FI/kKMDdVUpoZA3GdRKrXSZtFiGz4kJ9fRU4rGqTmyy4umZjiuccZrUgULFJUJZrJw4h0SanOh6ATK4Wy8OUU8n0uSwt47ss1g6TmrpqNCGVfbgHEUuY22md4lzP3Lpj1y6g/qSehyFhOHNeMXOTly5g4bHJ8ZiuMuB/+PwST53eMTvvvg81uy5zQNLcbzc3UpXnDaM6n+8FEem8KXxkjF5zsPUxONOyRRW56fHJbAkgYdqcXOm8OqjO7ZBJENzdhxix34R/euwWxoZy5rCTgMKUjE8Hze89/yMro90IZKyRIZJlm1iUCb2nFZYrfojN7s4FdM/KLZR3su4OFgMbpfZbCeZGfvV6vHF+uZfxor0BbTw2YKxprk4+WuHTTA/EZeiVCPsTsZHldW73HeY2dI9txQP+XLRoiBoVz54TJ81XUhJOkdRQthtlEP40VNSoQSVINnS1A5pVtZslESxaL0852aYY9ZCW8ci6oJlu7TKDY0UksUpJyRZgZNr0Vao2pnCxi089nu2Vq7fQW0aJ+fxxRGNeB0v2TVVg9dCPEfPcQ5Nn5yiJS8Oc3CY2RBGw/LYYB8vkCzZipd5tZB8UGsz2NHi94a5V/c/VZ/Aekgoi8XtLck70pmaW2SLC6m58D3Yp73u39mAE/tWAjID9knqb5fIpghk7JTno7Pe6jltfMbaj4H05/6L51w9vpPOM3olIdhVE6WxeWWx2NHSPbPEs0L5lghxLZbtlGoS00tphZ4nx7ObHdvttM4L62kHxKYrG0mfsAW7je1CbBo9ZcPJ1yCdJbBFSLAZCZRPavGmDMWisoMKv1TGIcr83ceeZ25HKpZv6d5jZ2eu86ZlTDoyYwkMRqKf73LgvbTjpXBH2CU+2b3LYBdGNRp/PVxznbZ8abkimMRL4Y5D6rkvHqv0/+fTlmMM3GmiTw0bqLpXa6TAVlgX1InGZm7mgVhEc7fxizKQHbfzhutpw5Qcd8eeOTjeDWcMPvLyk1uCsjlvjgNztGy6RULjq91jPcMoND1FcZ+K1vL560tytjw534t3tW52BqHrx0GCow0qF4of6Uvhxfoql3keYCd/L8lQZremgHWZeJVoKV266gafk6EUJ9JAn8i7hdxbZqewa53JViZxnynJkBQaxYBRG0Vj5TFK/bcTNvQy+9a5yRMGVB5zSu6RIA2Fpa3wRJotrN6/jH0ehiOYsMLY5iQirgsPC0cNHDjkjkPq+NzxETFbnvSS2hW10HYuEbPMNEWi5DiO4rnsQsK6QjSFMhjyTp7j9GyD2UQhhmWBHBszWZ97sZC3iXljMI1Ps6KDbQ7uCmmTMXowijWsAeQQpSO8NhuvMH59bfX/NZikyrGMLSdzb9qMXWb1ygN6H0L9ldZHeofp314zEWO05OTIS9VyaE6lLZA8djRs3ywcnxrSJzPZCJO46G0NYH0hP57EqPp5B5Mh3XYcgbQZW/FscIdBAufvnEDSGlYP9cOSMc6A0SAEA8an9QI+IVg0S8cTWKMSupbFt/tN2bJPHX7ZELPl2/q3ObdHrpOwBZ12i2MOZDPRGcO+dLyTLnjs9jz1d7wenuPIfHZ5SjCRp+6Wfe55ez7njeEZj909N3HLTdy0bnEfOw5L4Dh1eJ/Y9bNojLW7rGQpbzNX3VGeQ/LE4tgva8RZ5yKDF63wlDzv3u+IUS6OUgy308BFP/La9lbcqZLj2WHDPHt2/UxwCW+FiFUVSxmjqT7iHR2t5XCzgWRIZwecLbg+tQ3H+UQZhH0J6MX5Ymb7cVrhxpLe0OKVrSAdR0u61ENZl2TmePA6U9QfrHBrMhDEpaimfcVODtt1hGGQMZDpIO4DZrSNEOS3ixz6VNvrOlEw2DqjXZzmZevjmoKtcphJXY98aXIh62QcllHiZYOQZR+qY7acjYaxa3ZvQQPW5RfsQzyBhcVSdSqWQ+q4Tz3vHM/IxfBIr/GaNy1+6HJ4dzr2SVHCALZnE5CaqYQxhenZBn/tiD5DyA0Gr8XQuUwycmiwQ8Kd6OBLFJShvTbl4Xw6Rie8mMUKUGhP9lclTFlNYarv6Wn4A6wzZGMF6m8jgArXU9a9+n1ksq+0PtLFdvq2kU1YuBkHgR+qBsutL04phrKNxM5y3TvykAhFbpMH6WLTXuczRiDmmsrz/hPLNAW1DSvt5IiHdLYyhUvWeYiRi7hE1WjV90Ox/qzQVd5obFMy0Amc7Tph085TaEStZfGku8B+WMQcwkbO/CTepKXnc8tjHIVv69+Sma1ZBFZOrhlffCI8Y2dmLozk3sJqbHFhj3xqeI/eLoyaXRlM4uX+rnml3nsNJEjC7k26qQQn+rxFGb1zdk1jOC2et+/P6ENk181agMX2sbORwzZwnAP3+0F+18pwtomAhBq8cn7PtPFc9GNzosqYJh+KJ1KL3kcshcdPb0WCoRBS6EQn2S6LCkMB47EjHX7jPpcv1jf+ml6J2LlrDNgyZFJYoeVaGLKazZQTy88SDUTLYiWsfdjMBJ3zlYIeHCGnVRNgh0jptINGksSsLUzH0IhBlUyVcycF/aRxqOgbBmXFGsqsnXjtuvIKk9bDekmGjCWl0nzaW1JZ4MSKcpX+RC2g4jY305nITdpgc+ETu2sANm5WdYFpubWH2HGMYnfrXaYflrY/SAF3ynp22N1CGhJkQzz6FphQC9hpmLx1hWFYNAvY4PvYSJYAJtRuWAr8rPF8JmS4DQK/bwVRJBuNVlUZlyu8v1TOs1/5NwUhUFo5zOALZZOal3QeHfnwZQwWvsz6SBfbi8tj6+RKWk9F1Sczq7m8DXJ6YohYLYIy8M4rfCQMgjYkl+6SBgfnYsjRSgyfkdSfpgsrWVnFehJinRE06VE9BbVBr/y71O67aNqHK2vSz+LAGHxIcpFMttH/K2EhFcOYAzdxy2AXdmYmmNgsF2UGK2/zzsxc2SPBZFJZ552pWAa7nMyA18c4cxMZw62X+Lxt6LgvhmOW0IWiUHFdUvzW+47FalC0uvSo56oPYlixDZKXu1fY3Nk12EDybjOX3ZHZ++Z7LM9ZHV6KSIScEScppxDz4+2xSRJyWTNGVwnGCSw4O8kBfbE+NsvsIsRe2agCP5qudjUn4QMqByq8r7vNtM4JaF7hNfUnVYs/XdYVTEgs2UAya7iAOt1Z/fw3Pegpe7buLfCwAWi2tHp4b10XrVMt2Ujz2/4IAcpqZKdBgtqBRjCs0jxxjpoZ7NKuyasgHa0UOgkrWJJttqqnRMngUyNmGe0UiyYPOZ9xQ2S872B2675bX+LT90oP4NmqNMll4Wg1M4zS7DdTlDD40osbFLMR74LBnLxmAk9j5LVv76tZX7Mm0qywMfpa655vnGh8y2g+dIjJR7rY3l5vefKS4PbWF9JoYbKw1SKoyRqlE6KRJLxY8mxbocRnTNA5SK7/V9ZayPRXIyEkjotfoeD6/07gD7M4SinYrZ6SrCEdNM92SOJBqrMUIWOoa4tLmEGZtKc64MULxHPwYAuzLeTZYaORmK8i+ZFjDjxLZ42JbE1maycAxiLRePvcs7MTT/0tOyNkh8/FKxKGV/01Ywl8dnmKIxNM5C6dcZ8GLv0BR+EuDYw58N60424eeHbYtBmyMIgTmxDpT6Q/7xx3GOBqONK7yGtXt+zCzJmfPqDDC1byeuNupPeRR/2hwdaVaSzd7tyi+750vBDrOBvpXGJrFm4ZWLJrHsspWzWHX7BByFTT4plmzzJ5ytERq9h9tvJevVgfm1UmhzVW9alCaGwWhicuR+VamfiPZ9lDKntYeRhlqdpUWq7stBcThK52Y4slDIm+X0R2E2Vs4X3GD8JviFF9lL2wm4l17gpMorjIbhHjhmsvY6ttatnbZXSY2WJHPUC+tEhWt3ok58qitlndpVyDSutKSRKLnk9bLsNR08FKQ78cmbl0qn7Iq2NbdsxZpEUbv7RYPdHVCp9GAgYKOal+tdan8rBQ1SCFJtXR+Xc8YRjX8U9OvmmbQdy99M1Z4f5tJg+0/b46dRlXxFDkXUc+T7gzIV02DTQybsrZY4+O3GWJ7lN71+ZEFcqX1ft+ufWR3mHKZDXZZcXazcmbZCaHGZ3AAJVqn2n2jChO37IrVfB9OjetrNsV1ijttFNO3lTgwUmWDGYxjSjx5ZaxInmpAQqnVPbWDeeTeQPyeHPyLMU21vBSnJ5CRVtbTcMruUEcpIRtOxbPbR7Y574V6edx1zJrc7GMOeAo9FY0dFP2kjVbrNLq11O7s1oMTzJqa1hCPeXuwszWz2zcInICmwg2NQvH3kWJzAsLg4tNPlTjuSyiyXV1hq1So1NbOW9Sew5FHz9m2ywfq1C/nMzJs3YhZjHYFzrbj9dS73FTPw+s3SCc7CdJjS0q4FXHRzW4ojy8Paydkm3aXdtGJPXQ3+wU6zWv9oBR55EfwDahWQaaqHuXzw86YaNueCatphEyh6y/lMplimmPd7pnNQtaLaIJ2QvGIjr7hGVKshcsRdQHGdM0+PV1qCY0TRmQrGqOT36pE2QJ+/Dr5BWprISluu9US8cqwVp/7kQydFq//Yo6ouNDMc7Q97ein9rwWJ1zt9cKlMhqGkekGWGg9+c/XLH9SHe2ZrEcF09MTshIQVh/1gsQsvsVh7+H298CeZMFqijmRMiss45kCJsFY4uGCpjmalIjn7wT8XjqhL5uFyuvvYWiM9w4eoyX9KGm59U3sdTcxEEuuJKsUPyd6MJitC3cuZ7uzKbGZulpdSuOMl+8v5B/F8tL4Y5zO/Kqv2GwMqd1FHZmloxNs/DYHTg3kf/P8ipvLpfcpC29XXji7nkvnvF/3L7BJ4Zrfvduz1IcxxRYvKNn4YvTFbfLgDfCMj4fJo5LYJ9sI4ot2ZJL4GaSueuTzYGYLe/sd+y6hW89fy66PRe5XQbG5Hl5uKezkcfdgTl73h7P8FYE9Xexb25Q1hSuuiPBpqbVzToHetQdm7PV4CQsYkxihHF7fwZId+3suikZU3BdInvZDOLiGN5y2Hc/HBT0Yn2TLMMab7kYCCddXqFt5nkjHA5Gj+kSw25hxpOSEQo+tLHPpCS/zfkkxdVJKDqTJQ7yPd9HkhMy56wucrXDzFMQ3X31Ra9PdVBy0H3AZMSIZ5MZtouQqZQrUQyknepgS/X6Fci26yVrN0YrhMvFYrYFY7L8LqzQ+dbPLMXy2fElEtKhTtkzZc/n91dkDK9tbwDayGhwC4fYsWT3QH43R890DGAkw9aH1LrHUgw2JIrGirZDRjKSoObFFrEUwzz5Fgyzf7aBaOkejXiX2sFlGmXWbTaxFVRBFa0oRwzQaV6uKbCLpD4R+kjfn4SZVCctLb5JZUJmcgL5hyTwszZLmeVDfeQ+4sXWtIi2yiQ7NZtIHZiBZhKBRey4ohhJPwgDUNz/VKpjbNGYrExfZya2gDN8YKyuH5JiDMXph6cWXL1/qMJ2Q5nF5xdOOmTW2zdWc/15HdBbPTF6m5roPJjI1k4MRowqgonsjFg51k43A3NxbX4LtL+f+4neSlxfFbSDhBGchgvUlXUzsraQchZY2aymEusfWvRdnQPVE/CSnULEae08kTivNrM9OQmf2k/WDrbeb9X3etYu1p18DqpN3Onp27QoNSPayIe+HS/WN/uKBpQkb9TAv5wUqKymEDIc/DJt5kn3ear5rJt0O9zV/yjSUiHM2ok1EpSSd5o/AKxdrIbVF1swNVwgVbZsbWG1eQhlZSIjXSCpNDJUtTGs++Tp3mNtJqiDVEWgJCrUrSEnLrVkrTrfjdkypvDgGqsQ8mnnXM0mjIFmjGlOuvhsxKEpo8YTwr0pBeLisE6ak7pHVmi8FsUWIkA178hiYXlCgqoscXlzCsaBcw/tKSvBzdWfc3BqILK+1+tB6cOsj3SxDTeWw/MNtk90QxQW3kku6fHTs8DFCvu4LpP2nnBtWS7Bni9rxiTyYfR9bKeuUgzTIZAHwxDE/JqQ1xOx6q3MqU9yMoJKFX0uWnDr6dSGLObWN550ZsjbRRJ0ssU6GerPKUCW01ixRZyOQsYNmbPtxGU/8i3ba761fyZh8XbhVX9DLpbPLC+zsxODf8ZgEoOVU+q+eHKxBBM5c5lgErd5YLAL33v1f7ZCfOmOnNuRuzxwSBuCFt/ReGK27GeR/yyTWK6lIIka1maenu3pXWwX3MUwEmxi1tPvacF8Pm+wpnAZRs2d9WSbHpyUgRa9V4PqczHsgsylb5ahXSSdwtIgF/pZP0nXnWSOe5xDkz5Ue8+cpIuYnibpYF6sj80KN470OMnmvgg8m6IT9UA0RGijpJa+Va0UazSmoocxOqJ2WLXYgtZNmzEqCZzG0EZHWaFVRu1Kq21rtQ60BftOhxth7g22z7BJlKNjeNsxF+ClSg7K5F6yaSs72XpB8dLoxNRf2c9VR5ucbS5X1Ye5KgZe6u55KdzzSrhhn/vGD5GRlTCP91EZ08Vwv/TcTEMzlll0jloj6pzqYZdlJU5am/EhiflEZZklg79xFFdIjyO2S3T9wrjvKHtP8pmui4TdTIqOuJfgl+3lsRl2VBmh8wnvMzOylabJNs5MMToGqNa9nUgXKxdlvu0hQ9qp4UjIK2FND/lpdBAN6Qz5DH2I9ZEutnlQDZbLyiDMqNRL5iFuPcE1DZUvpI2eAGE9GZbVdaQtpdFbe3Ly0fvFFOmAE7i9FMV0pifQSoY6Ma6WGCutvU4lP6401uKpRZn1hWwEEq+n1Dq7MKbQ+9jYyO21KLbJeVKxjMUTzEygcCiW29I3AlVnEtbkFjJvzcKYzvjScqU2kJNE7KWOjRNS1TvTGalYgsssOmcGcchxLj9gJLeoPJ2RHmKHDVMLo64pP/K8RTowJg9J5AM1wWfOEr/V2QQaQG9xclvWtKCoZCiPyI5SEfOMXAx3c9+s4wBhFIIywBGmaZ8o8cPNXV6sb44Vt4K8lKKdbTTi9LbIDFeuPWghJkHGP21WaAWpAoS02DyATxCVbFX+J4PTbA1WJ1kpiSzwwXyxdpmV+9Bn3bhYlQ0GlrNCHlYeSeOd+DqTRWFkHjwXY/ID/kjtMr26LNVrstk0qkFOdXqT2axtaNep8qAa0BhTWKKM9trz0z22MpFztBSvc+PZrWSwYkhDUQ3xSZ6wL6QhU0PnRSJVyHadCZ9qZK3Na5xh7ayDvDf1wCTvjXw/Lp4DqDTKrlyZ553s4TVrvPJ+itYWIB0d+bD6CPxa6yNdbJeLxOPzWbw4Zy8wg8/MkxdjCoUH6ofUGDE3SI9Lm+tWhloupvnnAo3IYJxQyjuns5tkJILJFe2QLP0zQ+oN6VGUYjy5FlJAtBCRqDyfWsFMlxoYfZo8UqrIPGGdmFxhaCdDEaTDmcK+7SIolrGEVmyX4rjLGwYTGSx8sQTejJc4ClfuwMvuDmsy12kLQGcSn1ue8L/uX+UTm2u+pXvOXRo4psDL3R1bN/MLt09ZkmPXzU2DNo2BODs2m5ltp2EMWTS0GC2k2XGce2EGq8G5h0asqCflWhQPU+Bqd+S13S1T9EzJt672pX5PKob7eIk3iZ2b2aeOWQ3Ts5WYvpQtr2zuiMXyK+89loLdSbRX1hm8s4VYPKUU/DZRlKn9Yn08ln96JJsdZIOdDCZb8qIEo0aEgeyhhNxMEKJ2Z6bLLfklJ8c8F3abCWvEXjUXITulRREqIzO+7ISUtVqznjypCiMrSaecJVKRw3m1a8QV0iuzmFIoa9paNbwwGveWLbm23Vp8a0iKrWxkHb0YU9gO8rzHxYu8z870dqEzicUkybKlZte69XorhmMUnfBFP7ZifTv2J+M97eS1uOVkMXtP9oUcshJYDaWX5qNcCHemHuZzsoQuMmxm6Tpnp1D4qi+uoQXWFKzLLYQAVrjXD9LRFxByZCXNJkPaexJ+RSIRQtT28440wPipSQrsZFoXbkOmeDBv9bjbj0F4PJvEtp+5G3umfYfrMj7EVQBOHbrrJ67OFWuXWWnepojUJq+ic1Tz6rvYmHXN1LsYmSvMFhMNqYccip7QoPSpaXTRpI+cDAWRARTV2qFwT44WFtu0cuHRhHVZZEgGrMoDbDF4l4jF8s58xpQ9v23zJYJNvBkv28sy2IWtFeOKd7LnOm855J7X/XN2dmrOMBnphu/ShmASn9q+x9bOjMWztaKvEy3v2u2nU3F/ETJXix8ssnkIm9hxMw0EmznrJonSy67NeN49nhGz5VvPnwNi9+ZMofOxaW+Nshq3fmbnZjZ2ZlHbR6wU7DEGrscNV8ORzk0tjL4W9bPN1AKrY3TiCLRJhDBTSsIqyeXDTV1erG+WVbkTuEK80M3SIMEkpyuzkpWKecii1Y4yJ0M0jqgM+Wn2AnMedXvtZc6Yo4VZC2q1XAwnZMpS1jmwhg4Yi2jAixFmrVEY25rmXJUz2pXbVjDqz/shNgepikCNRZ6L61eCZjnhWmQMN3HLvcr+luIaQSoqQbGzwv6PqsmvB+sludbVVpOPadLoS69kpi6v4SvRYLDtgFFnysZmcnLE+0DaRjbbuaF/gmQaluaPII1LjUUEgfZTknxaYW6rXeXkZWy4yHtvdB5emzExDVEYfGfJnY6VfaYM8n6n2a71xfOhq+hHuth2m4VtWLgbe8zek4p0jzU/tsp9Tq29jM0YbNNU1YJbkhOGnsYslQ5xc3KlsVlr8DMgb7JS7dNQKBZh0HUSQFBXTnIirabfZVxDCfBFLqDFYo4OvzfYCPFSTnNE24hb8kfkLzFb3hnPeG63fMfmLQY787npVQBe9TdKkJLC9E4euE479rnnwo48diN3OTQW+1I876UzOhP5zs0XeRbPuEsD526UQouYZsBKbgJadyu+zqtFXUZMLubsuRt7dv3Mq7tRf2UpjnN2zabx1d0tnUqAjIsMqtWNxbV57c7NnIeRMz9xSB0p15O2YUzyOJuwcNUd2fpZ2Momk03h8ebQUon2xx6jmjmZM5cPzJJerI/JqoiXz9ght+xSEzLWl8YSLqPTA7b8WPVdB1ZHoqTwahbSY1w8aXTYO08eMu58kTCBaDGzjJ6af/E2t+6zbvh5lsJphiTmCbNq/HvdV2YLzrRrMCcnkXmzoeh4imggCAO4hYMoolOyWBnajTCmk0KjVcIHcJM23MXhBDIWGV7lX2zc0giKc3JE9BqbO6JyI2pHm0Yv3Wq/kH2idBbbidXlpDrlB7NxK+SkOBncnSPZQtnU1940nW2Tb+rbUdQgBAQxbAEwpgjZqdBMjMxkKX3Gbhax1DwlVFoxK4k7J3m6Ru0dQ5b3ZrYSJqPQfQ4fA4KU8xln1ihyoxDCYfJykegLaO8lacduZ7UlS826LMV6+pGTTtmpEbdGYtU5QNJZgcQsCbZfzS1Sr++4JmhUcXyTGdlCOThhEgLNOUrhqaLmGEsnHx5fZxPb2C6olKQoTD4xpsDj/sBVOLIUx3vxjLfnC4JN/Lb+SwQTJSBeu9cn7p6n7patXUjF8Ga6YCmeK3tgLIEvzI+4dEdeCTfcpYG3l3Ne624IJukJtxcWYrEtk3IcBT5yu4Whk6zZwxJgCTzqD3Q2cjFM7IK4Pt0vPXdLz3mYuOhGXru8bbPWWc0oBr/wpN83hvHtvOEYA1P2+BQ4cwKff+uZdMPWZK76I+ncctkd6W1s0qClWJwpXPZH5iQBBceNZ74MhD6umsJsWN7aYK5fFNyP0xL0ax1qGltWiHEx2C5hKCTE9L46wVXocc1DXRG0/Zs7QXbOFmyXKFcFFwRtyymsKY51LlsbALMSKQHptqpLEQjEmg1Mklrmzhdxfpo9cXIw6nP0RZ+bHvwRn+A6w3RIwQ1dFEtFnxoxqBTDnC3HKJ2sQ3gTdd0tUngrNyNqmPycBFaekkDQ7iRhp0qSwmaRw02d4bqsaJ9V+Bs1E5KiVqVU1hfSTty9qnOesaWxhav17WmpS4sj6uGEAvZGsmeXLksSk5XXyCjj2flEXBx5tM0mtz7PtNPPh8aghiGynMx1SzbiROY+3AjqI11sK3HJVhhA7f6KdpN45AUfjURJITMLIRtZKUZVg+XlwvF6eoyjbx/+OuszSq9HnakA+RBVa+W0BhtYqsuXsBDsZCWPwNM0vrWYG58bWaHZQ2aDr+4vWWnm2RKTnKB7G7nwR3Kx3OUNt3HDxs3NQeouD+11urIHdmZRCZDhOu1IxfDU3ZKK5SZuGtlqKY597FmCfLgPueOYxM3Jm8yEHDySMv6CzwwhElxiOcpj1nnQWTcxOJEQxGI5LIHzMLFxC0+G/Wq3mF0rvDs/KcQtxCoIxGIbfBVs4ml3R8JyTIGdm4md5OO2zwKo601mcIvCXZZNiBz0JFtXKQZ/b7HXp8OzF+tjsczDvzcpoJLojClymVfCTJ2bFpXf+Hofgo6FW6da1yiNQD83VGqpxRwabFkUNpWOdu2eT9N/AIGak8GMjmIKXRclPEO7LDtJp1WqEiObppQQJyYlR6HdrUpo6swW5LGTxmTWsZGQo9ZSdmrDmnRPrGleYi60vqCnphpdH4X9X8mnerNcBHE0VqPrlE/RDCeMkpOseFBbdXxLtdk5IUHVRJ4cBUGohyB/NNjZMEWDqQxVkLm8kcZoGT3MluxKQzUA6MW7ue71zmWSKyRLq/CuS7gPmYX9kS62+2cb0qsTfYjYqxnrknSgTtnGyjbLnfy7djPOJeZjj3mvExinF8KTMXJBlGxgkgF67Cwgp7a4SFIQBjGk9qJDM3uxVczbhOkyVTp0uvJGGW1VNpQMJXqWo4c+yanpTnIxl96Bz3TbhVJgPgTtquVT0PvIlD3XcSvEI7vwtLvj3I3NTerKrs76O7PQm8QX0znXacfn58cAXLkDCdO62Ou0ZesmXh+uScXybjzjS+MFYwrtsOFtpvNJjf1L81e1FC43AhfP2eNN4nF/wOts53G/5yxMxGy5mQfePZ6xZMtFJwYAUpiXVmgXLa7Vl3oplvvUY3Nps9/qYFNh61qQxdzCi69yOBJN5lZlQt6n5nBTLeDGp5HcvwiP/zitosYRJcuIx3QZ3yWJ6KwBAop2kVmj60BGPxtBpYwRRirJsDyJYAWyrJrWGjhfNCSgVGu/09msk/llug9073qWy0y5WPBBzPnn6oKnnJGU5LCbRyH15Isoh4ATD/ZyFrE6p62mECABAcsimc6Lk2AObzPZSJZts1nUtrsW0PemHTfzwM1RjGs+cXErsp+5xxiJ1mwKgyxSxvEgEPywmfXrhrQ48j5Al7EhtcShZKU7tyfjHecTZiMoX1rkPbE2kxYn75HOspM+DkA1EsILH2a5cOLkBypxkkNJ1oNSVa3QixTJusy0HyCDO4s6kpQ9vQYU+CE+REbnD1dGP9LFliSbrbMC1QDNFqxUAoTCK+X0pAiUZHGLkchKd5JLWB7G3Yk1GI12XlMzKlO5acSgdccfWCeQUQud18cw0VA601JGmpUkdn2+NakCeR4WKUBT8izeEUri3I1CiioWR2lhzw4RoztT2Oee67RlKWIoUU0tLt2BpXgmnc2eubGRI067zvbrnMyR68k4I65OQJNBeJsIeqLu9e97OmY9BdcZrzuxU1yKbWkiwAe61VzgmNaUjXrCBoG2KsxVM26dKUR9TrXjPv1dAElkiS90th+nJYk8Zu1c6kdCN+v8fu3kg1ktDyz/6qoZtc3QvqAEJtuKYLN7bYNG1iJemdHRtOJs6z6mj4vRA0K1nQ3iaJSzW7WgCFu28hLy+1RtpxaOVWNrYeWlnKzqIBWLdK9zlIKzolK2SfAemMYgDOiWD0vtdte99f3IwsPnWFTik5hng1g2mbY/N+Jr5sSil3YgqehADuveW6MHq0wKJZjJz57YNTYrX4GZncb2lUW6ayGv+nXu/+FGth/tYrt96ajeuJlNv3AYO+ZDkAKY9VTqC6XXEGc9ycyzxw2R9EplJpcT5xh9EwdhqeVFtGBzCQrPGOwQxTPZypuwuCDF0D2EQAwnRjMV4onSGZtesykD2E5zVs8W8mDh4GExLMeA9Zmwm9cu0hRu5kGcnlxka2cu/YE3wjOCiTxLZ2ztxNZO7Ezk3Cb22XKXJZggYfl0/w7BRAY74yg86e/5zPwKv7B/mZe7O14Ot9yngZgtn9q+x1Icv7x/Imb+Ot8J2iEaUzgunjk5zvsJb3JjIW/9DBYCmWMSYtSTfs/FZuRbd89FOpA69rHjV+8eNZlPdYfyNnNmJy7DkY2aXBxT4K3xHJAMzTEFjjHQOw0l8Ad6ha3r7Z9PW75wc0lwicvNyHEJjIvX90mlVeFFsf04rXjXYYe1IyqzY0m26TvtFwfsAvNLazQbTgxmSrLko1/no7uI3ea28eaoVq6Lo4wOe3CUs4jbRtJtJ8W0ykx6sS/M2WC2kfGTp+QfxbBtWQmVBgkzMBJK/wHf9QcFTDpOGzJhK/F5wWbCeWr5zylLKpcx0HWRwattYclERJZ3TEEStzaZXZAutR5Yg0scl8BhDvQ+0fnIxXZk6S3PlzNKtJrZq/wZn8nbKM8pJKZDENKSKkTmMWBdoR9mPbCLUUUqTolKGRcM2ZU2pquxqDkKG7lot2pNoeyWhl6UJAcT0yfMJlKS7LEry1xft/p+s86ey/te5pKlYbNdwn7Ig/pHutjmTHMVaqeykxeqnnCwRSEf7ZDU19dpQDSsBAiUwWaGdHJyMQ2SBu22dPZrTFkvnJPTYrPzOi38+pza6aoA2i2XsoY6x3qaTYaiySS5KPPQy4VSjR+qucVOZ7XXxRGKl5g8E6k9YMKokUXk3B5XQwtyi9KqYnaQeC1vM1snrOaaM1tOXoPTk3DKYolINe5Q4lPGkHVmWjvNFg+IbaxjoJ2U66rsSKfFtwYivL9DLTpnimqrF2wiJ4Wel74lCDmd8dfnndXhxtjyYI77Yn3zL1Od5WDtWuts9qRgSWHkpDOts130HzQtfiquzQ4f3K/+vSipqjT72BOz+6LdWJe0MJyMomwRy8D3GzXoXperg5092WP0dqmYFm9Xr8ugqoZF4fK6V9mTZj5h5Y8+ljcZXGzXMaj3cZKCXe/bIHPhKgOEVZJTv2+9IAfT7FbjnpOuvzLB64tntUt9cI7Q2xttQoSJrHaQ9fuwZgBX+2J9/5zT3N463z3Zu+seXY1E8sl72bp0JctZm1sS1K+3PtLFdnxny92T9QTSd9JxHvY9eXJrp6kvXoUD4uzwXaIfFqYxyJxGqfn922I2vbwRedCa1g/4CdywLE5MKVQrZ7Q4p6R6XU3goNBE29STs8+kxQu1PRui0QOBzXJ6Vu1tiRCPJyfwS8O2nzn3E28Mz9m6CYcEDgBkxODiLm+EFFXTcooSpezEU3cHPCRRvepv2J3NXCfR5IqT1Iw1maU4zv2kbMNNu9icFV3sHD0pG+6mDmcLL+/usabw3rhr8p16OEhFkojqXEh8jeXELAV6/Uh6O+NtErtFAu+Mos3d+hlvc7N0TFnmvDVez1KYsud+6fnMsyd4m3nj6popee5nMUEOLnE/BVJ09MPcRO8v1sdkRUO4EKOEfJDZ52m+dbwS21Z3b8XwQhEykFg7162EJ+/FCjElS3V8at/sMtkXiIZ8FzDbiN2t0qI2u022NQVFYszk6wV8n3Tjrz+j5Eor82J370jn6QTGlh/PxXA89Dg9oG+6hd5HMuDMymEBQfzGMXDs5Hg+Zc/NsqGzkY0TFUNMAiXHYgk2sV863r05Y+gXXj6/Vw7E6uhmTJE+ZbFqVCH7m7OF+OaO3ectd78l4Z8cyTWUQdlHosCQw7C1hX6zCCRfHbzMelCpj9P+XmFjJVxhDDmubUflbsRF3av6IuhiMaRoqKTWNFuyW+0mq7QoJ9v2d3+ZCR+HIILaLcZkOYwd3ie8Mu1K0CJXvTdtIbrcOlVJ2nE64JYTjkmGHKA41iJd57LRyAmm2X2ZDzydGt8mzjKsMwRYu+2TUxS2zhR+HdD/hFThfG7WaFBnsolRKdHVYi2YyFg876XEnWbbDnZhYPky1o7ys8FI+PpSHNZkHEUF7cIInpNnXHxjZ3+5VXNmAZYkHXFQklTnEnfLwD726oBVmLJrUHBwqels1+ACy10K7QIeFC72JhNMZnCR6Be1cBTW8qTdL8CuXwtz7YiryTnIKXqeAuX4oth+nFapB2RbmjqgoU4NpSoP5oCldYf1YG3bXLZqQEHvs6Jaqq2tjnJVgSBz3JMDfJX5FFpKTQ4G6x7auRr97JqT51o775IN5QSZM/UpRcdi1+i7ypc4Tl1zlqqFd1GTmlPpTypGCYi2XZdWIWrZcyVMpHa6H5j91g43C58mk8lDYXok3JqoxKP6WtTXIWcrKKRKl3I6MdTJwL0oRhbdP3O02siUNh+29ULX9ySrmYhTKSdOZrT56GGIrRM+nanXg44QX8sDXfApb+XXWx/pYuvOFpzN3B975ucD6XyhOzvSD8LkG/edDLXvxT4x+vUDnRfLlALl6CRIoJqKX2SKK/jKTraFODmBkwK4PlGyaF5rskSDi7IRY4x6cVX4x0i2LklNrbVTtj6Tz+Na2GGFmyp93xeGi0lsyaJj089c9GLwL8zjSDCRt6PMMZ0RctTOzNzmgS/ERwIpA9/RvcW5XfhcvGAsklk7lsDb8YKdnTi3R2aFoLfqn3xIG+7SwD7KbPU4ddT4sFx4QIqwuglt/cKsxCoQd6jOyQn58/srbsaBx5sDg4tkxPLt+jiw7Raebu6BVT6Ui+HtwzlTcnz64hkbtyiELMW2ph/dLAOH2BGLSILG5LEm81uu3m22ljG7BnOZdtEa4j6Q9y9g5I/V2iSMkRFG6dPaiXrtknRmmkNZIdpTzpRR17nZKsFRoWUjdqulEisnS/fMMr2UsGexbc6lRukFmVU6r0UwGTG4ubUsIVN8bs5ytZu1ah2bixFThUE/u7PFX3tMgeUxorstkK0815RqoLt0jONNLzBqp7PfYpqPuLeZCzOyTz1T8oxRrql6XQ56HV7tjjLmwbCfA4ex52wz4V1qh5d6+EiKNlpv8E+O2FcyPN/AdSCfpTYvx0j3mKIV5nKfcH1qFovGyuu3/aLsa8fSNdlTGRLWRWE9R9HHGoOgjzomzNFKgTYFu42U6w5/b1ke0WJNWwxghhxp+3Ktq7aTaEBJYftwH7mPdLGtcw1rC4RMGh3X4xl+EyU3sW6oSizIKgq3PjfMHfTkWi+k6mJi5M0wCLMv74RKD6tezFq5eNCEjUbvV8axWcRRCkuj/K+6ukJpR886S5ZvGkMLMcA9nCd2Xk6Rt8vAkh0v+XucGXkWz7Am80Z4j047XWcy5/YoUDKFwSRSMXxmfoWlOH57/wXGEvjSfMVL4Y4rt2+Pk+RIz10auF423M4DxyVIikclHxRDTI6abLUJC8GldlF2LtH7iDeJwS3s3MzOr7rYztW5caH3AjWfzmw7DZm/6Efm5Ljqjmzs6ohTi3HN4D0A94uYgp8FIWtVp5sp++Y2daovNK5g7xz+5oWpxcdpmYMnnlvVea6sUgkD1w4oGVi0bVThfDl4UpehhzI5cYTytWvVOy9qzzpZTIHUIz9fIWPlY6BIWNXcoyb9BpqGtxZgOZynxtKt0Xg2JErtirMhbfM6jy6c+AGIUuNw6GVsVkMQguR0V0i285GE5XrZ8NbxgsGvOvVU7EkUZuVqWFBjjOAyQ7eQi/hD13GZ87oX61YnlrW6j5oiFpnarODW+W1JFnsUBcIpBaloWlcOrMiDIhSVCCuaaPWk1sIJtJFfc5fSA0s8yyJHcoVipKEq0UKylMWs5kTOKNppdWQot/kw66NdbJV+7mzGbSL5eU94bplfBXueV4u1oG/mbCEU3BAVr68QAyt8VPgArOtDwg1LC3jPSs33QY01ghbvZf0Am9GJcXXQC1gtvUo1D3eZUtSM3Go4wbJaxhkvqULGZ6XAS4B956TjvJ43XLPhO3fi9vIs7hjswtUg+tq7PDCYhSt34NwsDEasyffF85nxZXIx/F+Hz2LJfHG6xJnMp7p3cKyFPWG4XjbcLBvu556jQshAc1qZo8U72QS2YWZwsQW/b8OsXW1i4xYu/JGLridjOAsTvUbieZPZdRJ2P2ffcm2DlZ970ssh4HHYs7UzTjvVVFZY62bZAHA7idPNRTey8zMbNzNlzz51HJaOw6FvuZhVwhRuzIvw+I/ZcveWfCmB8L5PZMTgpmotFzylmiAU2dBNMpjRCKLjMmaSYpAG0/JiQeHPqNavQNqu46e2ivA5ava1c1k2bt1DcrfuF3WfappPVmjThUQIiRgdOVlilcXUvUzDDowVZUWZHWa0uFmCU1yfmp+8tZlNkIjMd8Yzfvn5Y14+v39gQOONsJq9zdhcGuxc1QPdMHE/dSzqE12cRN8ZU3DZssyePGoSkkX+KNpXksGoPaIx8u9wENlRNgjfxRcxKMpGnPvqfXjxOXZedbrqf1zKanCBATck2b8Pvn2NLmN2SdyrTJHHyIZlsTKXvXXkrpAr4xzaaFFe9w93UP9oF9sC98e+icbLJjEr5r6MnipKNyE3eKYkxHkFxBZN7weFiknaCZ+tUiGDzlmSI83V1iuzqJjZ2NLuv852moG5npD8Tqwil9GvTOWCFnn9UyFoDSkwncAq8+xwzhJCZMmWQ+y46o+ce2Eg32YpNNYIUcpRpCs0om3tTMYZuEmB29LzSrgFYCyBziS+c/clCSDIHcFELt1B82xltnruJ17e3rFfenK2BJ847ydux4H92Knnamoa1/3StaK8KJxcpTvOFLxJHGLHqJ3pnD1LtqLZM5ldmLjsRnZO0keOKbDoLNaZzKU9Ns/mWni9kQ1goyEG9TT++cMVYwrcTgNT9HT98oAUUoDjJyLl/IX05+O04nnC4lXu56QTjRaC6ip1MlRswVSykiuUjR7c7wLFF9JVxG2iWLTWvGQ1obCzEYvWDEuorlA6f+1Ty8UtOPJGD3uVIAVrwVSkLEWLsWs4ve+qo9JJMXYrWYhssKOldIUclCntCsUXcu3iK8KjBFJvhbNxFiZeu7gV+R6a+BM914vHWYGRZ9XdSniIhMov2XK/H4iTF1mMrSYV8pSsS7BbpZa1a697XdFAGKuKjbgrJwcdj0mQzhN0mXi5zrzrPovPYkPZa2JSlXYqG7oGxpchyX67SOeacTBJB+3VJhcrr1fa5oZskAS1sF0SdCMblvlj0NlWVw/5u8xTzRCJoxeigFfmcCd4P0cnUJCmY1hN0bCGFgZsIye93TrKAYV5Z4vpEz4kpn0nHe4gzEU7qRF2RShOyFFO5QFyCGCFNUCfg9iQmdmAsZRShORgizCeS8Z7mbdMybNx4hoFNDMKgA4lDhmBm50pDSHfK1HqsZe56Fwclswb4RkJgWOdKZy7kZu0Zcqie924mSe9zHFu557eJc7DxH7uWsyXO5HiVDlAkwCARN+dDL2qhKfNkHQWNGfHuSmt0J6aVEzZywHCJygiK6JYyd40WeBoDa+3JrNkx828YYwCH4PA8DFrcLc+t/BopAzjV//5e7E+umuTVjJO1k5FTQ/sKbJloZST4qeolT1aKbS7hRCSHsbVvCJazCydq0ngZsNS9BrXImNDplgDR7F4bIRLhUMLtOdntFjVJJ/sJSClGv2fGjOg5jcNZlbjntwbNeOQxy1+JXrV5TVwJWZHbxMvDfvVMEYPw4exl8PImeRGV3LY6shmiJOnHESlsRKIND7UFUJYWBbpCFO1QtTud1HNr1g56jw6g0kGNxrsDOlMimgt2u1kpHa53ooPcg7Ci6kjL5CbGVtwXSZlAxMCX0dEPVKkaTM6ay4OUZIU0+SfJVl8H7Gqbvmwne2HK8kn67/8l//CH//jf5zXX38dYww//uM//uD7pRT+7t/9u7z22mtsNhu+7/u+j1/4hV94cJtnz57x5/7cn+Pi4oKrqyv+0l/6S9zf33+1TwVzcAzDQtfFljeZs3SY7lZp3XXuqic6LC3eygUpms7LSan0mbSV/4Paoh08y+Rlc74TO7V49KSoguaQiHcB9prM0RXM4xmuFriImE3E9KkFCVS2W5zFnsxtZRZcioEhkc+TEDa0687Rku8Dyz5IfmyydDbxfNry2cMTbtKGhOGlcMdTf8e+BPbFMyopajCFQ3G8mXru8oa5OJ76W576W8YSyFie+lsOuedn7j/N5+fH7LMEzfdWTDOCSUxZYKEnmwMX/SghAMORV6/ueGl74Go4cuYnzsLEZT9yNRx5utnzeDhwHibuY8//uHmN59O2MZYHt/DScM/ruxu+4+odvv3yXd44e85lGFmUvx9M4twLJPz5wxW/uH/KW8sFN2nDmIM4UBnRzB1j4Pm44fm4abPb33LxDp++eMbTsz1Xm7GZcYCMB7ourjOwF+trtr6R9g3QWf2Q1AVOWaxqjrAsjjSKIQVeZnkE+b8JGc4W8tNZrt3GnjWkRb3Wu0zZZNIuE88z06MMXjrQvMi81PmE75KMuHTOaI0UAbdbCJcTYbPgwtoBk9a8a0xhnoKY6Fc7yKKErVHCCcxksQviSnVwEisHjW1bjo7lvpNAgxPHrIzhmAK3Sjqcs6N3kU1YuNwdOd9Idq2lcL6Z8C5zO4oJjjGFbjtjz8VqNi6eGB3z7Jj2HfPoWyeOKYIo3st+WorBdWJdWd8js4nQZ0qXibvMciFmHtbnddatemN778izBC/UZCPZ+zXDN6mXAdI4GVcoZ1Fm7jovLkHGj7kYIXN1CbuTfZwgOmjbpSb/HIaFfvPhpD9fdbHd7/f87t/9u/nn//yff9nv/6N/9I/4p//0n/KjP/qj/PRP/zS73Y4/8kf+COO4dg5/7s/9Of7H//gf/If/8B/49//+3/Nf/st/4Yd+6Ie+2qcCyTRj7XZCK0ACW087p0vnJmYxD7pN5yS7tp4q8ZWJZlrCRynSdbqjnKSaCYWV50GikaO6XghaVkPmhYBhm0bM6PBffJr15IV+uLq0ShH09zGLzG1StJo+JGHqY/LNNPzcHhnMwnvpjOu0JSFWiBZYilX3KEPGsjMzOzO3PNsOyay9jRsOudPUD2E1r45O8jhbP9PZSC5WHJvCzMYvYvivhCaR2kTOwqREqEjMlttpIFaShRF3mDM/c+5Hnnb3PO4OXPhJu1M9EBkx3ejVLep+6blPPYfUnVg65va6AifGG5knYc9L/T3nYaJXdxxrTmMLX1TZr8f6hto3oM3ra9dYzSlKMYIk1f1DSTfYygaWJJ+wWQQSPZGqVDtB43KDa0soq8a+3Yb22KfJQTWExPske4jOH99vZeic7E8p2jYKaZrZSvSqiob6+1ZznlNETfe3mmL2QHdbJDovs85jeycOU736IBtTGLzkfae8BtKHIAeJalAhPsLiY1D3vfY8ChIKUI19bBZCaBGiqPVlNaYIhdxngb/bL7a+PiaxzlTL+vtXwpQYVpzUCe1w2+uvsHEzGhGQUfZytXesBjh1r3E2N5vaX2991TDy93//9/P93//9X/Z7pRT+yT/5J/ztv/23+RN/4k8A8K/+1b/ilVde4cd//Mf5M3/mz/A//+f/5Cd+4if4mZ/5GX7v7/29APyzf/bP+IEf+AH+8T/+x7z++usfuN9pmpimqf379lZmjiWIKf5xDizH0EwsyiazdFI0SzakkxltWRzdc8dsgYt1YzYur+k9hnb6srv4cFM+2ZvraYxNosbg2SGKWbbRYHUVPzfDmZokEVdi1LJIJKDp5INUKhyFEhuUyZxHz9RLnNVLww2v9LfKIj7wreEZb8ZL/vEv/RFeP7vhB1/9zwxuT2cMCcOsBTSYicdOSFRvp3Pm4giIA9V37r7UguXP3NiIV/vUc4gBawrnYeJu6bmZB0n/KYbzbmJA5rGpGO7mns4mvmV7zVIsd8uAt0KseG1zyyv9LW9NF8RiOfdjc5Sasuc2b0RAr8XWUuhV73fVHZmz44vHSzqbuAoSqzeYyKe37/JSv3Y51bP15e6WKQfyzvDZ/RO+8PySTT9z1c/cHAdmDfpO8QUb+Wu5fjP2DfjKe4dzypKNTmaCCr/Gg19TwLqM0243KdzrbCF0kU0/M85B7FoXp8xgHUApXGwPthVbqwVo0SLQPIv1MB8X1zZy57Ky+gM5WcJGeAZZyU6lCDJmnnfkXSKczVIooVk6Fgp0MJ9pkXBFit0kc0qSoeyihqdrZ17HOu2wKrPZwS2MaYWJa1BIHdsElxh8bHvpEORQu68eB+g8WTvCkg1xdpTJYc8W3FVm2QfS4rHnk7zek9oz+kyJRmarGj2YF0eOD9238Jl0KeTXUsRVy0yWsl0TgTBC1sp5neE6nwRtWGjGJlUnnJDi3Mhr+vp7L/+OUW1rP6T73Ffd2f5a65d/+Zd58803+b7v+772tcvLS77ru76Ln/qpnwLgp37qp7i6umoXDMD3fd/3Ya3lp3/6p7/s/f6Df/APuLy8bH/eeOMNACE0oafKvJ5qUAF5tUOTUw3tFNRE6qUaha8noLpODabri198EUq+PbmN+nAK41g0c+3kps+rWcGdFGoZzNdTnnyvGXXrSU9uqL9PlR7o6bMydZ3eqeht0wND8FwMcymMxXOnJKrOpPYz1bLxLm9I2BbPd8jisiTwrG3OTHXF7Bij537quD0O7fuS1LMKz221WkQgp41fNAZwJlidKZMbyen0Z2qItZhqeDXaKB+Y4VYNcW8Xzt3IS+GOl8IdF34U5rKafmzcIsJ7PUTV02hlh7/fVP7F+vqtr9W+AV9576iMV3MS6Va7IVNMK1BtS9DOsIVwmA/OPMXh6aQRVbi2/v20m32QClYgj04lMSdwbhbzHWNFvdBQsoq66d6Sa6GFE1hV/m27JNC0z41IVPcU48UAohKHTs1q6rVmT/gYVq/lGqlXg+Qt63VZoWTvpAgZp41Kld8YHvgKWFdWmWbzg6ahAA0eb6YjNKLSg2UQiNdmkSPV17+9N+ahBSYn710lqOrjmtN/v+8xoO7B8vxisk2b/Out31CC1JtvvgnAK6+88uDrr7zySvvem2++ycsvv/zwSXjP48eP223ev374h3+Yv/E3/kb79+3tLW+88QbdM9F4NshA4YYaBG2DxjeNYhpesoEuM78uWHyLfNJ0CkDhDKDY5jRkBoF2yi4xFelOqzUjxeDqfFXRhLioM9XiFJpQYbWVD9ZyDAxvOeKZJVabQO1eq3uMKQYGgTFMzVjUNzlmS2cj525ssG/qLK/6a/4fn/x/ce6OXNkjAO+mwGfml/nl6WW+e/cLPHX7Ns991d3wZrrkp+5/C4/9ntfCc740XfH54yO+ffsO527kS+Mlh9hxFqQQH1Pgbum5PQwcbjaYO4/9ZGEX5jYn3YaZTmU9U/LczgNX3ZFv7e95EvYEG1d3GgQan7LHkTlzU0saOaaO27hhr2YV3ohX8lV3ZMqet8ZzcjGcO4EaLYVBTT7O7UjCcp+GFjtY4eZ6YKkOYrvzEeuOv9ZH+8X6Gq6v1b4BX3nvqE5O1grLWK5XMUGgTy0+L1fGrAaIVF7IFF1j8LaAk+tertGtGNXk3QovVj9ep6SmFNVjOGTM5AhvBuK2EB8tTUsbZ5lBurPURmU5C8zd7t9AOvo2snK6r3HbC1lziA2eJqpu9TzJvNmlB2OUmmfrjKBJZ34SUleRAjumwP3cEZNjXCTC8nyYCE7GRzeLqBO2/cIQImU7kdT5bVo8yyQEr+0wM7lMDK7NU0lCKMtFs4R91hg9JVoNWebh6spFAbqoBiEeXMb3wr+YF796I1SIV3W1sV8RrBoF2KIUk6EkB6o7rs1bY3urRGlZ1vs4PNuS77+JpD9939P3/Qe+njcPT6QV58/14gh8cEZhFSqw0HJniwErcErLhWwn0vUxjJXu1lQxc14vQL0xJYvQu96+ddOzle/rCTP3RfxWqydqqFaSRQy1kY3AGPleTqIZq4YSuViW4ujtQjCJQ+6xZAa7NJvFPY5RmcqP/R5nMmNxzRM5mNh+xppMRpi9Oz9JeHvu6E/MxzOG+6VniiJfMj5ThsSmWzgLUzsVe5tasT21dxN7Ri9xfCbhbD6JApRTdDDijLXgWIplH7vmDCXa3MjOT9gkdnISyycf9lRs+12CEer/IXcsJ6HXNR7ssKgndpaLO7wIIvimXF9p76iGBNWpqKimUpI7VJpyctvV7Eb2gsoCrnCkMSjRRg/MRqR7tQMyVCRNSFS5zm/rjLF+RKuW/wTZqlyPUhAG773KGltndoKIGQQlq3Cyfj1XUw3taq1LxFmUEb6Pzdu5doXeJjbAXew5xE1TDUj3SwtjOY2rrPyZmCxJ9x2n15W1AstXY6D2PpQVdSx1T65IU5GvCQLxvjewogon+29Rg40H7Gx9DKMyrNi7tbMua0FtDU1lLuf1+znJe1ZGRwm670012/wrdMFfZv2GFttXX30VgLfeeovXXnutff2tt97i9/ye39Nu8/bbbz/4uRgjz549az//YVd6bcSaFUamQsWLxY6WrMy2Cr2wGHBg+pMirRCuDVIW4qgvYp9W/1FlKGILhCKMv6qtqg5PRSn2GiBg+oTrUoMq4vNONGJVO/tEyRXR4DaZrl+aXjjqB9C61Cj+MTpm4wkhsvELsVhu4oZPDXvO7ZEvLI9aR5is4TYPPEtnfHF5xCe7d/lU9y5jDryZLngvngHwshfp0Cc6ibvb555Ld+Ryc+TdeMZN3PA47Dn3I188Sof77Lhl0ni684sj/ZPIt12+xyc219zGgVwsG6dh0aVeuLl1le/M50zZ8a2b51z6gxRdCr1d1A3Kc5cGbtKGu2Xg2bTlsAgZ6iKMbNzCa901h9STi8XbxJIdh9wRs8OZzBmGS+1U35nPScVw5qQzdy6zLJ5xDDI3irZtHC/Wb876eu8bIEWraOdojk5IOsVQTAIrrN4Wawcn7kRCqFoWJxtxMRq3WejOZgl1v+4oIdM/GlvIuLEagn6UmbCpMKgTr+54piS/0ZK8/BHSViYtVjW2hXzwDF8KpL6wXKbWPKBs27bOBDky+vi5jqqCSCFDSMS3N7jRkl4voHPJJTq8SXS2gFv47P1j3ro953wzEmxm0cJ/uRlxNtPZpFatpcXzPbvbscyezXZqcqLgEtuLUWbVRUZ3KVnaBEkPKjkataQsFA21fzDiUTSgzaEVmqYIG9w4s+p69es5G8KNxUbDnAOlU9JaMjLX3UXsNqrvtTy/UjveIs1bOXjCtSP1ltxnhrc97gj7T0fs5sP5qv+Gzmw//elP8+qrr/If/+N/bF+7vb3lp3/6p/nu7/5uAL77u7+b6+tr/tt/+2/tNv/pP/0ncs5813d911f1ePYkFMDUjrQY8Jnc5yZ0bi98l4WEpJ/JeiGsZKTcYCR3WqgzLJOcAk3ImNliD64N1HNyRM2uZLbtBGldXk9KaN0+umYWfnqytUocSOr/2X4XVhKXdaURjabk2aeepTjG0vHWcsnzuGNrp9YtBpO4dAcGO9OReCdd8Ln5CTdpxyH3zHqcrvF8FXIFdWcqpsXuHWLHlAQ6Cppy4vRkW20Tg8qFztzExi1NvjO4RcPjhVW8cQvPlh2fGx+30IOdnbRD75iKaHB3fuZxf+ClzT0vbfbEIvPjrZ05d6OG04uU59m85bP7x3xxvOLt+UKfT2JjJTpwKY5YHDlbpn3H8nwQaYCrF/9v6KXwYn0V6+u9b4DOQ+t4qc9iGXjC5RCFwdpdovNYq91tnfNX9my9fkuB0vaZh4znpDp9O64ESAqiIT1aUR1UPkhB0ohuA+XoKUcnZhnZEIciDlP1I5vXGWJ73gq51udUTffLSfNRvAShlFh156vXecxigRps4mwQOHiMnuCElNr7iLeZOTuW7FpHbJAUJB80UEQ74qptj9ERFVGo81HrkjKOixyAFmGVFPVEKE3FQTtcWJ9XVnCdpVZSqzvZ4xW9TAPEjSQ3FWUWY+X1oHbUevv6npa0WvqiQfRVqpWGQtogz/n9dPGvsL7qzvb+/p5f/MVfbP/+5V/+ZX72Z3+Wx48f863f+q38tb/21/j7f//v8x3f8R18+tOf5u/8nb/D66+/zp/8k38SgO/8zu/kj/7RP8oP/uAP8qM/+qMsy8Jf/at/lT/zZ/7MV2QUfqVlfUKgW4udLEktzozq4krNS9RTqe1SO71UzVtlAxqEUl90HutDavORNEshNYPIeRgD7mhYrkQGECcn3fRBAg9KWCn8y+JOKOcGu5c5bu4UttZi66ycLPOkNpJmdZsp+qF0mmpUP+TX84ZD3+MofHG6orcLv2PzOQJiP7ezEzsNkrcm8/n5MV+YrrjwI+du5Km/w2mhu0sDz+KOS3ckKLV/KY4zKzPU+7mXAhhmrAks0eHsmiKSsPQqFbr0R8YceDdLB33uJzZubkk/uRh+4e5lYrE8UQvGK7fnvSLd9FIcS3Fc+CNX4dCey6/uH3M0mQt7ZDSiAQYhcr07nvGrzx8RryzHIfCp4V0GM/EoHDikjuu4FbONZODWM7zrGF+L2M1CAZYXxfZrur6R9g1AskhHR+kz7mImjV6s/RSJqqYUeajEIul0pGuqB2j5v3cnnukF7GZVMOSMzv8EHnYHixsNy3lp5vkmGsKdIW5h2eR2e3frCPeWuNWRk/oExMvV5H/N3IZmz1gRO6NdoLJqTcgQWE0euizbTzSUrHPgYsga5rFPncRZbjNv3Z8zRSdadZfYeHGQuo+dpJApAmBNYdOJR/qS1iKcsyEuHkzBGim8Er6+4H0iLU6ew1FDXHpRc5jJUUgC7ytj3IUsUX2ukE1tiEwjhXmfJC2ozl0L5DMNm6jvJ6xEMadwv+7FvhPfg2Wx7QCGz6StkQ7cZ+JZJqlRCPFrVGz/63/9r/zBP/gH278r+eDP//k/z7/8l/+Sv/k3/yb7/Z4f+qEf4vr6mt/3+34fP/ETP8EwrNmp/+bf/Bv+6l/9q3zv934v1lr+1J/6U/zTf/pPv9qn0vB26zLLINBCUbNwMxvYKcxy54Xo9FjmiBWuNbXbNdWrGPEnLussxrpM6SDrSbYk8TuuXp5xcpg7L24xGQkXYM1jXK4H7MFCX0hKXUdPaCg9PQ8yKynRrsN/5PFjdEzvbaDLbC5Hluh457Djtd0tOz9zn3rpBPV0tRSJnUrFikaVpPmxMo+98COvddfs7IQzGauf0K2deOzFg/iQJWy9t7HZLTorg58pefZzYH/s6LpELjAmzz72XIVD6yKn7Jmyp7exfX2wC66Is9Onzt4jZsevHh/zPG551d+o7ncNp55yYCmWCz9yZie+4/xtLdhCVBCmpMxnP3X2jLMw0TWWdiYp1H5MHdfzhiU7vM/Ei8jkaAkfd2+eU+67r/rz92J9+PWNtG8AoqkNaY3QNEU20toVIsSp5tOrOtnx2ElHZQtdJ7KXafHkbKUbMkbrXGlGEW3Gu1jCaPB7Q9wZJWDK4TxuxK3IRInozF72mTgU0kaSyMxi5eTtVy5Ia6oeQK0nv6g9MfZX9URpEqWTn9efKcryB+hsZE5y/XslGqViyNFLIS2GOToOqXuQl1v90G9HmT3H6BQVyKRoWSaP0QAE0P24onhGrBnTXVh/L50x56T2mlmi87KRPduGTDp4/DNPvLQsPpGTEYKqOoMZJbiVurc2Ps06vzXKkam+702vCdKQRaNgo8iQihcUlfQ1mtl+z/d8z2pf9mWWMYYf+ZEf4Ud+5Ee+4m0eP37Mv/23//arfegPLIH+FMLR9r5k8QN1R8NylgRuOFj5INdu8WS2Yb0M9eUUqqHvBZIVjZcQZ7LaKVottjJLqHpZf5ACWZxexKBYv8XfOMK94fh6hCEJNG0q2cFgZ3WeqZB2nWHU9zhawnNHPDOYq8KSHMvR8XS7Z+Ok2NZIDGtKg4al2M50JjEXx4gwcrd25qm/bWHzIJ1hp5DzTdo26U8wiYRlygGvlPpJ/VAlg1I68kPs2PqFp11SYpJV2NbSA2d+alrapMHTnwjPWbLn//3809zFnqXav+lF58jsc88xBZHxuJlHfv+B521V2vPJ4T0+ObzHl+ZLorpdAcpo7rmPvVhIuky3nUk6T8/FEJ47zPMXOtuv5fpG2jdAocYh6qFZUQ2fxXlp0TngKdihXWianERtevXi7haOU0dcnOh2WQlNLegcnftFsRx0Iw/ISqUIYbIYLbYV/g2ieS+9oGBm1pp4eghQ+LiSfure0zr006ZL96vmE3xqqKGrFJiy05FQ4h70ms0NlWq5t6qzn2fPPAbMeaH3sZnH3I296oNXeLdkI3GjXhUe9fu1O1fI3h4txULp5WDjfSbONIlnMWj3KoU4ZU+4NRRvyeeuMZfNbCHp7NqW9TFAiKkajSgmRfkBBG2yEb2yogaSpiQHAkLBnMQIfpj1kWAjf6WVo2WK2oGeLaJTGx2EQrQayGwgXiTpbIvORA++QQPFiatSSnJ//pm8JPGJmHUvxWhahsgCbMiwi1IYJ/FajjuVlFQyRYEyOyE6nSfSoHBEWU3ESzGwjSQnNnE5GzXWME38XecoyyM5gY+Hjn4jlmnHGPil+5d43O/VJ/mewS48U/JTwvLE3XMeRu7SGXd5IJjIY3/f9LVvxqsGAU85cJcG3lt23MUBb4TU9N60Y0xB2LvZMkdHjG6dNZsi8p5l4Dps24w0mMQnhmuZ8SrDeMyhFdPFSDd+ESSb9zZvmLIYZ5y5ia2b+MJ4xefvrrieN1yEke+++iUw8E68YMqBVCyXfs/r4XnzXX7k9yzF0ZnIXdrwq4dH3E4DN8dBDiqLo+siu80k6EO23H3Cks7nr9fH9sX6BlhWUavGtfCiky+deAebal+oSgVXM2ORgpSibeYP22EiBjmsFVhnk0qioh6kgelJZr5EZDuaN9vM7luXqak0vpA7Jd8kg1nEazl52U/afmNo7GQhE6268ZINZXS4W086//+x9y8/l23ZXSj4G2POudbae3+viDjnZJ58OQ0uuPciDLhU0LWl6rgBLYSEhKBJCyTTsdxAsujYEhItEP8CLYQQ1ULCElJh0EWWi6tSFWXAZNqZJ885cSLie+y912POMW5jjDnX+iIfjixh7MiIKcWJE9+3H2uvvdYcr9+jIFwuiCm32bPW6tYZESEIxpIwe2D95HiF2+MOh2FG5+pRWRin2SrPFAriIOi6jH23NG4uAPQubhGc3lMKIyRBuVgAJcynrp1Puo9gsba91pa5K+pxkkf8WF0YJcPsBZUbMnh65s+9S6BdQTgsKCk4v9bPUeZHCn1aK9pNN7I4+pgn6zAAhtWx78zVBn0Zr/nNrrm3OthqYeRsWUlMBYtTOTSooY7r9+PzUQWsHeCoZCXPIBlNjJxnBwn7DaLijj4LG+2HrG2hMPMCs8nyEx4d4Za5PQ+dWNUNNEBAhbUHItBg7RWtqLpgc2Ai4/4BAAbPmP3fvc9DsnCzqtvzjIEXnMRoDgWESw6NInSUHokKOnLgggfYUaO3ay0YHnOP+8UUoJgU9/OAc04+fyFXkXn8PRThNr9BtEBfW9aACVPUareu+v+7sCBxaccQnIp0yaa/OuXY5sWjRiTN7bGAVd834WRqLzCwV1HG0fnH93OP49zhNHbtuJkUu5RRPNgu+xlzfh9s37XFQYDF3L40eHXorjkqRvED4GDHKoJiFL5K+xElpCBIQVq1pzWhrtz+TSdNdibgQJVXP62shlYlLQaW0oPrAVQFPLXgSdmMBL7vRtyu1yraMAKyJ4RonN32gt5GrRZ7BGB2kRoB4TR1mKeEPmXEQA15nHMwkGSysU6H0pDHdQUWIAJUFMXntMSCkGxcp8ua0FSHJBmwVu7REgB2fnFrj1cf8uDZgs9MZS+gTOCJoTvTvVcliCv1qRD0HB9V/rVwJS+GmhuRj/McamO/38rv+ndrCcs7UNliIZxfDqAkiMNiEPgdGppXZ7YT6Qg8Amx2EddsRBerajlZyzlf+olL4sbHlslIEqRUTIkFNvAvZK2F4bOAvFMsHxeHk9u8JezyesMRHs0COMiGSA8wPdbXpKpgwwDRCggIQXA/dbjZjbjuzGbvECdcR5Ng/M70BD1nfJDuMWqHby9P8aJc4FR6fK37Agee8b3l2gNixm3Z4bdvv4Z9nHGTjC4T2fxypxIx5YiihCXbjCa7rGEcFuPUeStpkYDfe3hi51QJ+zTjz9/8Ph5Kj++NV/jycIevDy9wKj0miXiZ9wCArw0vkahg1IgAxQfpAdfhhJtwwp+6+AxDWHARZzAU/88vfgZdyPi/P/v/uADGiGfhAQMtKCBrd5G1dkZNZsOXI2bfGFLKOPQzcgk4zQlzjuY+8q0D6NV71593aS0PHeKljZFKklaxELsQvc/nqvhFxXGIb7AhmuPL/XloXNLzuWuJf85eMVd8hle4VlWZLKucI27+XwnSA/ffXDV6aSFwJuQL228kM8BmDA8H8lCBuQYBVkhUkE7d1/L6OwBYrgz8aahodu6qzX9181mLML53vDQP6mgjGyIbX2E2U/g5R5wdR9J/YDTE4nPdiu8gGHc9eCBaihkRkCtGxa4AXcFySsBCkJ1CSUCDHSPOAVoU6lQ9LA5OCrq2nJVM3/hqsTb9GEweM6Hxeat1YhiydRDglKhgKOyayIDMFCbEgjwmgBTywWJCRGF1L6uBWEd3kLtaHnGNf9R6u4OtB66q5GQXj0CriEHNKKNPwIEVFOCD8jrkaG2KtJl1+AXIqqC4ufHq7zeLFI3wXjl0TNoqrgpRVz/umhlbJgUYYdg/Vp1jbKg/BLSMtMqDVSP57Vo0gFWbdOO97hrfta5qSrDnGUUZs0REEaPGuLTiIgHTRoas0mMMzIB2bESKOccmQl5PcRE2Go9E03itgRBW+Wb/jvZhcl3khEAFPS8YeMHg9J6rOOEqWhIwyzP73C5Naeo09vmLMhaYzvNW/rHa91UZveSz5yKhiRpQQZP+fL/ekbWly9DmfiYFgXzsg1b5ia4Vj7LJHFaluOSt3kafqRVXZSH8gEurcvy5eOfMeb4A/P/re3u7lw29bNX2D3jNLSIZaHtQE7fojOKiwhD112XYHF257aOlsAG+/H6uQaaqKAXfu+rnq3PbxZ+jWgCYutYuPXZFQmYoDBHdrAx9n63IbLB9xrodb81gWiVfhUCcv2xdh2DbvXcHWht9DKCFIV1p71dFSMQTl+3MtYLJCLSyV1jBAhSix/PwKojxhlKvb3ewjYJ0NUOUHKAg6IYF59nspKh+YzNDkqJ7drYLZeMI1Fo1kyPXvL1jGqnYzFi1ZYWq3k4KCtkVnH8qo6pPVQ9LSEUgmhFB5bdBnd+7uApMWU0KKkCqHP1rcXQk3wcsewE/PbtBNWPZn8FQHHOPWSJu0x6BBOfStQv8JD1uyw5P4hFf6V5i1A73eYdPF+OhPoknCAgf726RJeBuGZpSVNVbvexstnmcunWe4VQoXE+42o94cbdHniO+8tErPN2d8CcunkOU8N3zNZgUN90Jhzg1ZatzsXmPmd1bG+pBh9YSHmhpQhe7MOMiTEic8XNPfg8DL/hyvMWoCZ/nS2s704JXZY+T9Pgw3jfeMABMS8Q8R7M0BDB3xvOrtwexIH88v5/ZvmurLyi5s86SGChJ2pwWjunQRmkpo1VXfArQTlE6sT2mEJZ9afKCIIUEF1XYiC8onGXQZFcZYODFXyi2Z0wW9DUq1IUcqo2bUVNMCENZgYuNlrBTV/CqQxjJgFZOP4QDeYD6vkAe1y0/DhkxCZaj7UULRxQfYY1zwp0O5tfq7kJEQOoyQhDcfHxn2us5YDx3kIcE2md0w4L5nKCF8eSDe+y6BUsOhsxeCAC34qGasGsQ208cvEpBEa9nazUfbXaNwbqGWExyksRwoQqAemuBS1qTbHbxkcN/S+hfKl7+bIe8z/Zd+3y6ocydt1sFS6r8btVIZtbWKqZk/x6FoMyIsYD1zQRx3u5gC2vn6BKsZVxFr3XNOgBYa8VPFrMiu+AFBCs0PvvFWy/SjbHBI9FwGAq6mR4QQH5DblHOlN25omxmDUpN49j+jfa3Flq//Npymu25FQhRA60UwiJmsTcEy6ofSu8CE/bFV83k7XooA0ZJDdpfZ6m9W+bNEixx8aqzCpAXBw40kfUNinEpbJzCKI0Ubq9nnzGS2egFyKM5K6g08XLAKlNrBdumUzsCiaxSDdA2l64t4zqPPknf/ow6AoJGd9p1yxpYCThOXetOmMdlWEVE3q93ZylZq7hWNrXKAdBM2L3KqR00mhj9C8ZyUORro+JwBkpHUOLmCgOsnbFHq3bU6gVZO3GFALW9wkA5MPEFISxzbJ27+hqcquCCtzJh4iwaYccJ8mCLtWrj1w7GKS7EakmBB9Oq4VzBQlXAfyseAcBbq2gIf0kC9v23VqN1pl28BV85qsC6p7YKtJ0bq2DrjJVHhuxkld4VE+NQYEWI54DX413VPy89kPe+B7t+QZvNVgGQiKYOBphfcO0uegRYTxtpM1jQUqv2H3KNvbbe+mCbUsYyR/B9NGTvQRoISqMTx6vpM4CuX9APC5bF0IKAnSwag9Fwrr1KXaz6kaoKIzbcJzL4Pzwjbs8nnwM40CGcGHpmyF6sqvULv9EMwubilTpXKOBQsGgHzIR4G+wzfGS2U8sY2+s8jD0+o0t88+oFdmHBJ9M1Igk+7EyC8ZP5BgMvTfjhKD2+M93gLpv7T+LSAvRFmIwiMw9NDaYPGSlZ23eWgHly9GGXESJBkiGmj+cel/sJu7Rgcc/a2oIyMYsFX+5vjfNadkhUMKSlaToXEBYHPE2SGsALgAXYMDfaEAcLukfpMYrNZC3AJgN7SfJqebGZrTJ+5uY5TjnhuPT47OECr55fIO0XDLvZhN7PEeE+gB/ezJPy/foJWRNDQ7T7sHO1uYVtdkswn1PfWEXsXu9eBnzwnzLuvxZxH03+jwpQdmRsB0/4AazgI8C1kmHvlT1wuh2oJesCDAX6qkP/acD4kQDXM/QhQY8ROpR1ryDzV83wJBGWCGgvKDsF30bwTJAea/DatFVB2kA+7JTH/ZMz1Ck8KRU82Z+xiLWT5zEa6yKKGxe4IYJa/N51C/q0QA8r5mEMHbSCqIUxzz72up5a674Gw6plIBuELzzQYwzoXzJmNZnbypnF9WIzWU+Yym2ygqpbBSusEidMPz1hLARMXlknAMU7k7OJjBRHYdeg2flY4HQcoPCJQjteG+dxUBSXi9xSvH7UeruDbf2M5PMM8owpCqSqezjCEEoY73twV3C4GEGubK2OYEYSn7XAgmhVa5lDs4FqFniziVGQZ7JCLpjtohUNyFDXpgpu/X7Who6ulWKVd6ur7BxFfY7+GDi4wjM/WCCsTjyRBU87E6bIYm0qm90yTq7KZDKI0yrgr8Zpbf6xpBAyc/oq37YUc+cA0I5PRJvrSRdNrzlIQMelBdvIBdGt9EYNeCh9Mxz4qFvc/i6jEOM6nrBIxCfLDZ7EIzq6bYYC1+GERNkEOwDclx1GTXgog9n0kQlYAMCp9DjBhD6qwTyT8f+IrC1fCtuMyb2GNQCStl/Y+/WTvnhi4NIDYpsJWtLMUZuikGgwzWEhlEFx//WI6Qkgya8Z0hWU5JSSUoVpKjCSFXiI5rizk8ZqADwQe1tTWCHJXocJpoJX+TkuBAWgqSPRUKBjAM9syW802ckS/LGbjp4WWqt1D3hVsD9GL7c9+PUxIwgjkOI8ZExCzQXJQGLAOCcDHYbSKtjggZh8vmxSjdS8opsqn7fbKwujdsHq51OFJT4ELBfW6ePbaJrGcXOfkoKCz6P933VvlsFpXHXvrcG8/q32/9Kb/GMI0kRIKqgLQDMiANAq32Y+EdQS9umPwGLvf/aiYKg3ZkFJ6mLfhNAXyCZoUVDIHBA/T8iXDFxYFqaOWKaFoXtDq+Fk0HC+WOxEnyJwMLPoaTH0Kp8DwonA2e6DrMEvBDGO7JDNHsozKloI2lsgQwW/1XZGzTSjtEyzDeGvihHhXyZIp9BLs+4K0ZqsoubCM5eI+6VHHzJkRw7MsgskUcF9GRpYSWCi/EyKV8u+GUFPJfqcw915HIVsYCITWycybebsMP4QBDEIBg+2BzLh8QIGqylQVeWol3mP59NF86t9Ek+4dNlIALjkMz5ZnuB37j/C1/cvceMG9z0v+DDe4YpH3MmAURO+NX+AU+nxxXyByAUB0t7rZd4b5WcZsCgjKzcT7OCoUJkDZgUwmcyndmqyfO/XO7PikVA+9s246pmr7SkxZcxjWsdCHojzdcGrZ7IGZqeXLOdkAbt3etB5RbhWTme6ZQyfEY5fJ5SrFXmM2QBXGi1Rz3ttVEHuC9DB9iChNjcsC4OjotvPmKYBPBLk4EpK+7ICQ6suc2HrxMX1fasDkSlSSfsZkTYUcsVtPKTecA4bsNQyReOb7tx0pAZut+3TxtpwEwVShEFQSkCZGaE3pHVewnqea5ATm82CFPnDBfF5wvApY/xQUK79PlXTMEZQhIM0hS6MAf0XjOXSuorN27xbOwn2fADB2u2pK80gXoWaKUk1nTfKkjaAqgiBWMARKLcdUNWu/qBr7o0e9cd0EelqFOxt4mWOFoCTtDlHdcPIlwVIivHcrbZaQaGhtLZRCQoIDDAFAJ20k2zoYc+ayB0raJ2pYgxrm2Qo4L6AXkWEM2HuXBjRtUsfcbM8gOYlYBmr4Iba8Qns/VINyNps9oqwcWA5NNP4RQNECMdsvNoSqWkNb03Zq/n6JAEnt7F7mHsENmWcFAqiEhZSAKFV9YWotdaLz5DvRhOMeDqcECljlojsFnmijE/0GosGPO2OOBezyxscdVyXeWguuOnOSFRwlL7NXReNmDXgXna4LwN+b3wKALiK59fkHSNeLXscc4fIBdk/W/29KBoATpawAlI2JPf3691Y0qFp7a7G5JsZYJ3nbeVVt6CkVP1lfQ7o6nGo3S9WqzwXE9Epg+L8JVilO7G5irHae8P3m6p77JaaqxWcd9xcJe/xLBYWnCttKIodC7tanvtj84khe4B3BWX0MVhfIF6BEqzy7KJ1oqr8K8F1292jb+gWA2hOEZIZ51OPEAv2w+yWe2jvex5Tw3M0eoyfw3KKKBSNU1wTFRMEtNn1aC15VUXpFdNToFwI2AsZEetImUNQ8UpTIJ0g76s4hrSuBfWmFlVjAYXqEW772HjuTANfCFOfm12gWSL6uJDWfVtKgDgf+g9NG/mP0yJeM6pKEs9LQEylDflVCOIC2HRh8mx5isZDy9zMBWpArX14TGxoxL60FqqIt1460ypV2tyALjFGhcAFWJIgdRkyDejuCMu1yY+tSGhqQhgcFKlmyFPwG9FbKeptkqTO+90cqxiPNHjFCQCzRCwScJ97d94JTasYsFktAFeNsmB0O+9wXhJOc8K+W9Bt/GjrJbKdWVTD5ZJtrn3ihFwYT4dTU5QCjBQ/A7jLPW7SGU/SCVkDpmzSkcaPXecdiQoOwTSbT9I1ylIBYUFws4QLfG+8whAWfLm7c4BU14Lu7TLgYelx1VnFfFy6VXdVDf0oi2f6NVGqo4b3651ZpVMEgt2T1T6v3lfVpLzyYmtHqqCBKGNXHCiJxjJom7nARjh9xpw78IlRdoJyqeBjMNDPFdYg7m5A6ATxYJxR8WrQfLdhzIouP6KZ1KAuEa1i42hhMrgY/zKZ/GQ8E5beqrayJIQjo5BV0WVhUBQMu9lVn8Ta53UcFARZbD+97GfDZmBnbkEjAReKFFfMgwqATMhjsk5Bpd3UY3bhH1pMzAIC5CRAEPtCxIBi6kJ12gvyTsH7jJgK5mNleMB5uwqBgNSM5suBbM+ManKN3gZnNoc2YEPXUWvlZ4VJdQphOQTTPmgxxOU32RguBp6yrihnF0l6g/VWB1sRQp8ySumMTzWbxNZyVSwDqhlhzWA9W+QkKBL8RBMEAXAderqPIIG5RLjWclOLKW4WAHtNu8D9ZsymvwxSuMiMXewfZOQrE66GYNXo7GRt8wgwjd2a5RGadCPE9D1VFRIYGfCAR00ko4sFN8MZHWe8mPfIwhhLwnM6mOF77jCWhCEsSCT4pFxjkYCxRMwSwdCWeTJpI+kDwFUcMZeAuzBgWQLOx25FR/rxl8LIrI0ydC6pIaMDKRIJjrnHMfcQkKOc7T2O0rfK8zbv8WI+YIp2WVbk9H0xWtBlGBFI8PXdyzZzfig9Xi379l5ziUawJ5tDH+cO4xIxuuAAsSJ0BlqrtA8KCpL3beR3apEC8A3zLkJ7NSeuGlxrqzhsgoSLQECB5ZRAsaJSLSnmXkBEyP6c+ZSsM1XbmVEge/hsdHssWOeV9b1agvj4sLUw9GRVcElWuWlnGBGZNy3Z3RrYwMBy6de8sDvYwIKRU4sqDqQqRM3Z1NcCKfZpQfD5agoFgQUXl6NZ52VG32UM0UwLlsLohowSV53hqoG8LD7/VoL2BbgQ6Gc94kTIdW7tSXC+9Eq3fh8++650HPAaMJfZRn9aDKeigzSZx1J5utsW9YaZQtGTpkKQaMp/tZ1cW9P0EKHR6F6SBOItckS1EVT/Zon6Wx1soQZBr8AXngjhTJCBIZEbQIG74oE1QKOAuaCQz2mKzSU02EUaJrvJxBF71Ve2tmm1wvsftXL8RiQ1VZc66lFCcB3QMoZH/F6KsgEEkKH3nI5UKTYUxYK7Z8pVSqw4CpGoQvAFQzBd0jEnZGUsJeBE1kKdS8Rcxfk542HpTcDCP1O9werf9pG0zTqje8aq2ryzAb7i6o0psgIdsrIFcCWAjeIzSTDxDJJWXQPm7FNgtl4n6XAsXTOEP5eEc+lwLslAC51Vv0/Sqck/ThI9uFuwrUCvurKDoZZTAgVF6Ir5Fm+BI+/Xu7sKIcymBtcUmRjtGm+Ulw2aV7N3RipdxOl8plKnq8qRBw74PJZYPTBSq4Yf7SXbljEciOMCFkoOUCouR+jj1jYXVr+WXQJRBxftEG+Tu/qSlNpR07ZnkVd9hPW+VyXMOWKXzC6vJvY1Mb8cJmTXSu+iBWAU84tOKSMEbsE7kCKLCcg0b9okSENGoW4tMHhzruNr7fvNeqTpDKye5RV5nUzyNsQCSaGBzKowiWNjQSxmcJABAXt3y7uhZDRNzYQwecHFCiWuvi9WEEVeAVp/wHqrg21MBTEUxCiYkqBcKcoVWmZaDYmhgBwTLv5rxHKpmL+pa8BQ67m3ud6l+x4uhGoKLMmkyFoh66/bKjxvOfFiyicaYHOJMSLtZzs+AYQCkLFmYZlAE9vMpRPQZF6XkpO1Ny+zBdyBVnJ8IeScELqCkOwir56ycwk45g6BBNf9GXOJuJsH7OOMq27BF+MB5yU17uzdecCuW/AzN88xp4B96loArnZ1gCGbF7fJiruMfIoIryLKNRD3NnctxarJyMUk3UrEWCIu0oSb3S1ukgGYXiwHPOQOny1XeChmn7ZowG3eYZKIQ5iRSLwtzI5IFggI//vLnwIA/Mzl5wgQnMUC8SmvAAUmQ0haQsHoYkGWjCnZY9RBH4w1M6ZPe/Dd+zbyO7XIkld0guVptnvR6YIUFDqhieIQa7ODIxZIDJDgur0sKBwAWdkEcZ8t+Vw2iZ+3HWko1q722S5596x1rzwJ51Q8ufYg4K5l1ZKvBekKABI4i8Jb4RVzsiurbWCGqeu5GIcm13WPFtBysSQ9kuCQVmEYAOidz387DVClFoSHmNeP6CbxAFaHNTXRnlLYZqKKplVfCqM8W1BuyEwghNpM1qQuFei0IYyLAhjIDWZo1Vb2rbxW6cFldpkFabeg5AD+9mDz2S8v7fwIM0rWVcrX58Wpy4hRjB4KQAajYPI+G1jtIQFX2SSChwzp30zq9a0Otm2zrFmht0NaNeg/b9JoM2wW4GITVBF+hBXBVy/iTTaluuGEb5Ks1eIKeGSN99r8rx3fFhSlQPNI9JuFs/3RYFl2y8KqMDcpVNi0TNOaeTMpsgtGGE3H3qcijUUZjIwpm9ZxF7PLL9rN0IdVVm0sZjrApEheYW7lHjmY7Bt5OybG0qTcanVZVajMC9dfy+39XsE0kR9yj4UD9mHGosGQ0UpGFfIWM5NAJAK15byYOlaWgAxDUE8ltqC8XWOJKMots27kec+AC9ZWHhUCMt6vd3ARK9AXqK6dp9dbtwSs7UsAVfQCHlDs3+vGEGIBeSuyVamZ255ChNZOba+1fb+6X7QXfPzelcvfxGVI0Tg9dd/KduDUm9iMJfn0/R9u808iPNL5rQFTQAj+wOwzz1oB1+TcZFHreAsbmowDK5tG/Ibzq2TAVNj5qOpRVVSonVOxjmMeqIlXWEdt+wX5HrmhO5m5glEZKftD6vmq6GpHY7M7xMFRx4EFhU0sRFyMg/y817jBbNZ/2r/Z5vFWB1vAvvyc/UZhMq3P+oU4N6yMAQiKu/81g8+M4feMSiOdcVnVSe1UCPHeWjT5wwV1Fstsc8yY3JR4jBas9wZYUOdZybCKaHBXmr/lMkfLcquTBNYLTwaxwDUGxAdGGIH5aQGGAnrwr2cwhCFobRXZ7MArbyV8fjpYKxhAlg4PS9d+J0o454Tz4kCm3Yw+Znxp/4Do1WviguROPydYhVut86YScRhmk2abErgryE+B/mrC5W7CtMRmN2azYLPSO6QZkQvulwEhCfZhhsAUqr4z3iCS4OPhFsfS4//44mPs0oL/9eZT7MKCp/GIz+QSZ/+eIxV88/KFmVe70tS5WMtcQHjWnXGTTvjd4zPcLju8PO2QhZHcraUfliY3WR4S+BRQ9gXUCfIHC2S/IqPfr3dg+cZbN+dKc6GFTfCiF2gQsE+bTECB7d6PZrUpfj9X6b/sQMzgghWxy8ZeKORUGPbXAfDK7k/+YAJShkRxaUYPFKhxUxsVpWSjoNCFXatmamLt4jBYq7d80VtBEeEdM296khrIMq0jnFY/kAlLXAwmTpOVcVx6vDjvEUNB8s6Zbh9PCoa2kdXsPtfV5KCdZsVGBcs+lGINxm3dJ+swXrioUG1zqyGT0z2hHLwt/yjIAqEvazKihLIEqGgDz3IQ6M+cDNDNCimMXKwg08ygYME2+R4QgzS5RyaFDKV1MnmfQYfccC3f9zl+xHqrg23JAbnoOrtQrDDs2ibyNjIIlsFmWr+XDbSeqnxjTSBr5kr6w0+oX+h15qC1pePzFctgud0UUKwKM1W2kQBazFSaFCa5FtabrlXNPrOtnw3wGa63aopYFdeF9WYKpE14/6GE1nLexQVDXBoNqKiDlnweUzPW7EjhqiSsWMXWEbRlsDEIIh5nxUyKjr31tAyIXAwdLavZAbuW87mkRjlaXDISMPehtKl0Iwm4VswbEY4hLOiDtam7UB7NhB+R5oEVeFILAbG2FMXHlfH79RO+qvCDr625BoA2tqnLKi9eE/latNbqiGBVF1Hj0tvr1udRu94A+r49pRYGwFpJ272NFkiqQw07n5egfh2vSkxVVKpd36MfjNhx1uSCgEe2dURG8dmaD9RjLJvqtQgheKNLYGhlBR7xcB/JocpGGhFoHT1EOw7dnFdSmG84waicXrFW0RlltcfUufYG7NTOt9iITqslov86epJRA/D6hPXzV0CX1s/s+ytVVHKh5vlbv1txINWbrLc62MqrDtMTQ7pRZ2LWfDaRAg0KncLKZw1GnZFOsBwYZafQXWkVLc3mvCEJNrepRG/RNfOtm3MSyxwnfqRnChe6xsIQVhAZobtx9hRA76jkemwMdC8Yh+8q7n9KsXxoNlMcXOy8IhMXMroSo3GKi89YAJurbpGDiQv2ccZ1N+L/+/IjvLg74CtPb/FsOOKj4cGcfdTcd+5zj0iCPmREEuzj3PipF2nCzAHfvbvCNCaUU2ztFhHCtERcDZMFb8+AmbS9zqt5j+/cXeF0YZn8fe4x5oRvHF6g54zfuf8IAsKfvH4OUcbLeQcmwXU8mxZyt1jL2dvkAsL9YpKOQ1iwCwuu4miSjlzwtDshkuC0dDgvCVM2d595Svb9FTJlHgeVVG1Zff0mfL9+opfuCojt3pLFuKg0u6ZwdB6tA6BECHJ0XIAj8K1rFSC+J2hZW6St/SqMMgXQObSRVtVP1sHYCOKa6GgjKWqJvmTjq5LrDcfnyfa1L5VHiQKANi/WXlCCJ/GZ0D2Pxqbp1N56l9dguBjYMRzmBpACrBvWx4ynuxPGnDCVgFzss2ZhFLFxVfLE9qQJp7EzkZsoDVB1GjtD+jqFEWyfnxanOcWC6dTbXhjrXhggESgfb47zImPq2e7bKhYkBDob+liSuIPRqnesgexzO02xsjhqgdJa737uATThnmWJpnSVA6qdYskMmSI0GJuhasVPY4dyegcAUtUWjciCowYDG1Wi+Oq5BAMWxFqBYqXueOaEWLNOv9nqe3jGmb09wlGtDVSzmfZAbTcFLU7Ijl4VM9bOB7s59TZr7hXLpc9uiwUEJXXXH6zz5Fq+ezarBWs2CVPS6kNuGWoXCjo2WH7fL7jsJlxugA89Z2QJeFh67OOMyzQi0urdmIVxGSfkwDj0s7Wpqjh5NmL7XWH0KeOim+x55K1rT9MZii4WTCXik/M15hLaMScqTXxClH1mKxBl3JcBe57RU8aJOkCBXZgfzY+jg6cAtLbWIUxgKJ6nAwDz3yyFzUnJk4RmQgGsc7P5zbLT9+snY20NwLUi7H9AvqX1PxV0eQ6mnlidYfyeB9Ds92gARLwSrWjg11+7YgjGYBv4UKACa01HAXvLefs86ex1ZAprkKj7jldZFZkMWJesDNuhbJ2j1irTCgARhoi2JDmygNXup6IGelIWQPiRQXwWbt2vvlvnluIFQlNcirxa5amfj0JO2aF2fpQVpcMqEuTdwTaXbp8Da/Ky+dPmxFj3bVkMAc17k9tdfARYKVHw7y8vwdr/pJjOCZrZWu6Edcbsc+Xso0UiIM+06t3/AeutDrZhsosmBAG6jAWAcGgtBhr5sa+j9/ZNcQVoqiwkUOaVxO4bMrG29sO0RGvT9gvG0q2ZmnrLhi0Ql5nAZ0IJDPGhOkdFqTGucn6jy74JYbkUlM4UqcLIyAMbjbUr9kW65V6thOtGAa+2iWymnILgyWAyh1kYO6/8Ptw9ILLga/tXuIknvMom03gIC465x/PTAR/sga/tX6Fn84q9ywMmifiwezBf3MseD0uPL2LBw7nHeNsDdwkYCcf9hC/tH14DS9hstgsZT4YzbqcBn91fIAVTqclqwKl9nDFLxMPSI3LBZbKg/WI+IPUF+7AmB8/SEYEEo6SmgAUYmrlHRiDBk3jCdTzjLvd4FfZ4mDrkHJBeREhwzmMdF9S2XWbgvOn9vV8/8YtYLBguhnSF6/kCWLtJqmslFBV0YhPGF6C4AhRVCo7CaDe1spXQ+LDYqNk9AlIKIdwHC6K7DC0BdIqQvjTpx+pSQ6woV46aPlVTekB710SGjaw4Favqim1O4ipWfAy+d8jqWuaVtMyGuq0c+8pC4Dg37jyXgLLh39f7fFwiuljw5ct7HJcOcwkYlwgRxtCts+W8BIibmSCqdf9mfsRdBoByk1ubG7ACQmgDZqrnhKnZCDJvEMWsQKwtYYWeo4lO7Dz5f5nslAYYXmZXPIBGpC6DGaAvOoSFUL4kNs+tQNxi4NqshP4wW2X+0K+t+j9gvdXBNh8E0Wcg4j6rdA4mIBGMcKyiVgHTOvNsEn3bzLACE8Y6kwzWnrhYwLqBscvaqmirJoqbG6l+MejEgmSd2bTZxfen0RrN0OBRJlfRh/WGZm9xO3fMwFuKfZobPJ9hQQwA7pcBhzhjCItVfZsMsQbkb16/AAB8b7zCB90RN+mEizDhIkwY2FSoOi7onNAegjSovpCBkNjbxgBwytYyHl1vee/v/6X9fUMOMxTnkrALSxP+jiTYhQXnknDMHZ52oXngThK9VZy9pWzHfpcHPJ8u0O8zPgj3zXbvJp0RSPFFt8fUR5wP/Wau7ifAEystBKH3rj/v0pIlgH3vpwK/7/yXVKtVbqpSENvc5xsbRWG2tiZFkwFEUBNQ2FZXhbwz5e5itVu16WqVnaH7axtad14QuFg/MRpfVZJAwcDk13Fvc03JDBKvDl0xCcCGr7oGMwOMRjv+KGbxV+egsIDb88pOiFQQSTBqbK1jAppuuvrYCP6zaTG5XMOH6Cra7005eyAZurcaPgCgU7SunhdCtVWc6zntC6rfLXfFO2holScBDTFesSRE8P2X2ueTi+Kt7JppY+U812tjJwAx+PMOMijkw7Od2yRtDl56ttb7Q0C8fQeCLa4WqMam9lEtk/KVmvQXiwepsAY8eJW7gYeTy/WpAuHMZv5OQBkIus8201Of3ZSNlNtr7Y2aLSoDKACpVagIajdeDbb1wtPHH0ci1ptxG4ubuAYAtkpeyNROajb6dDiiC6W1Yq/ihGPpcJ97fNAf8dSrwrqKEgoYuzDjz1x+gt8fn+C/3T9DxxlX8fwo0Ba1wDbLCrIKycAYGhXJ0Xs1cL5iaSpWHRdcpAlf6u/w5f4WD2XAqXQGjJLOK2lp4Kwdz3jIZveXB0aigtmFKwY2a75T6cFuu/dCD/hiPODj4RaXPDaLvmfpiJ4zvpuuMfcRp0PZJCxo3ElmMcQov0cjv1Nr4ea8ZZzTx0EQxWkmTOt1EwV4tgBzMAOBYL8wbV5/Xg22jgVpwB8CiGh156neqjtvtWajmaT9jDxH6MJmVB60WXuGKMY1pQBERdovJuQ/hXV0NvOqUlc1kgmVPWcBaWLE+4D8dKVKqqLhLXZhvRe6UDAWA1nmwg2AWbtXdVWd+iUHk3ysYCsY/aYG/Oozrr0aB7awffbJpBvLXswggD05geFx0pCtBZzZ9OFjQT1K3lTctb1bV+gLJK5z2nQ5m7XqbUKjU2KTJCmBdhmiERffjch7oDxzwRLHBdFkrAYujHTHoLsfMH/4AeutDrZ6DigXwYAEZ/so+cph4G5dBTIwREMqq8/rAizAFoLmNTMpBwcw1Rswu9QirN+v59huIrgIeSWZ69lkw6QXUDbQlfrNqn1ZZ4b1IvV/awRULKul3nVE67wC2gzlw5lNu3nvzj+kuBgmXHYTnnRnRC64XXZIXNxGz4LYTTzhMoz4ZL7GMZvYQ9yAkC5cBrHnjMgFk0RcePv2vgxWaZYOWQJSvYmKZ6xdaaIa1Xnnpjs1A/q6es54Go54KAPOpWsmBZPGZseXyF77Kk7AgHbT38QTdjyDXTP5v5+fgaF42h3BUHzlcIuLOKGAmxY0YDPhrxxuISA8lytUiUkADeymYE+i3uyGeb9+MhaPbFWg1uQbdk+nOgNFq5BU2EQnoilAUdCmGiSZQMSW2G83bFaUYZVorTPJprpWZ40AqrCOwtrNHAXKCpkCykjgq9KAWiBAL7LxPytuJErz16YqMykWsOq4RHptoEYMBbnujRW4qY5G9gqgKrM9LD3OOfmoSnGcuvUcsmDnreLbacB5TsiZkSIhErC4UUmuNqZRbfbr+vPzQ9cKD90JtN/cgwutynyeR4TOzAVs7/PnFcZyiq1a1Z0gXU6onrllNrUvcRwNX0+IqaDceNuZ1mQgZwuiacjIQTE+tRZ/8M/OvaJEgQ6WqElhLB9m8xt+g/VWB1tanMPmcxftBbTLBngoa+XJ3vLUJXqm6dZ27M467bEeFGWD/HW/UyJ7LI/cMDXkELdysAqa3LxAkwCZwNnaHsow5ZgGygAsmsIuvGLgKOpMtLvRa1gNMekXHC2WLFQD4xgL9mnBPs7No/Z+MY/XraPOPszY84xzSbhdBnRcEIPgIowYKOPAE0IU9LzgNu/xUPrm+jFJxFk6k1sDrdJthU1BJ5TWBk5U0HPGRZwbhUewaiUf2AJ4RUHX/w9QHDzQJypAsMBaP8M+zOg5I0BxkoiXk2khR7b3e5qO6MnaywWE4txbJsXTdMTLuH+c4AANHFIRjG9qAP1+/WQsnqlRX5SBRmwlp4Ft0OmqAOdNR4rUWqCV1qLU1Kbq4wkwpaRiQMZHer4+vqr3slb1p8oLJXVpxWjIXW/F1jFYGvIqHQsDA+mMhk+xg4CBs7wNqxveag1akldKUn1fJnEjAsLoojFjtjARWHCeE0QIMZqFSBcKxhwxzgk5BxPd8UMQV5QyRDBs7h2Mo1zO0cxe6tgsufjGYpV56wTWtgAADgUIeGRqoMWwOTwbfXIhQA7c8CymnEXgkyVLuDHXtJhsnzXEcUWd2x6w29k89nzZQYMiebXMsSAIQzubj4sS4uUCCY/Vtn7YequDrUar+CgqcL1YYDxvAmryfn79cjrLNKuR8lbhpXK2DLVG0JO/zinYPbBbQJ1A9mXl1zq6GclvzqKNa6u9IKd1RlPdOPKyucD9pqNiVWu+8LbP886UpT6YrGXSCYSArBa0mRW7fsYuGSjoEULXhSkeco+LOOFL6Q57npCo4CJMkMT4sLvHPswW2GCC/wWMgTImbx2vt4zNbS7ThKIzrpLdQPfdDjEVpJRRlHC/DDhLZwb26QhRwl3e4cW8x/eONgvGDugpW9XshW8BI0BwEesxjj6jTeh5QQGh56XNYic1nWfRiM/HC1x3Iz7q7/HFcsB3pxsc4oQAwatsSlVf6V/hK/tb/O6HDziPCcuxa+e9bjZ0DOCH9zzbd2nxAkuogbV6qtx3wO5xIZ+B2ixRg1owiG5mMjGwEIQVGtZ7sJqENIcpMaoLJ/FOmgs/bAJoTfabKISjbasJOwmtynBOV9IxgHpB6Aoy+1zYkbxbJ5qmyVwIy11n1XuUpt5UzqHNXo1nu36WF6cd7u73uLk6oY8Z8xShSjgMM7qYEVnMtOA4IARB1y820xVauaobvmqrplktGZm9a9DLiqHYorfJEoY8xZbcZ1fjIu8UaE8oHaFcwJIUt8qDwlx/MqG4sUxiEwmpmvrW4eLm4FTfNwRBeDJZRe9We8scEaIgpYJM3j34MSiDb3WwbTJnbLONUsKKPt5Aw1tQrTcT+98FjzI7wB1g1H5F4nKKfvPQ9kKoCVd7n/o7XStW/7uCLBT+vuLt7IoOEJ+p1CC+mM5yUYLC3TiCQNMK2Ais6OMKZDDgUUG/EYGowaujDHaD9V2YcR3P6HlpEmyjJgQXmUhUWkVZQEhUIEToODs9x9CKxNK4eYY85lbNDmFB2Ugo1qq4gBGcWhAgzbknQNCTmczvecZJOiybS1OUUardnlOEVAlZgwlyQHBWcwjqZQEYmBycVW37LofJZkpH+66IXdazeBb9vo38Ti3rEqHtEYAn6ACa+EShRi9sdBTvQjXQka4b7tZ/traSTdLVf0+baqy9xuY4FHZNBrGOVl0b1kHdQ1TMpk47acYaxlbw46TH13O93o2WWNYKvb0HHiXYFYU854gyG8e2GhQoHABV9x53x2GWx1Vn/SOPP2PrIgUFeSKhdbxXD6gilHX9PppX+OZ7asmRV8cVRNXofbK+HrnSVzsn3kIusm7FtdtVmSerPef2e6yqXiby8abr7Q627uKicH4awVq43q5o/LP7BJoZ/S2hdEC+KaDZqkmtcm0JjV+rAMKDXRDSaQNOyBRAxwi9yA0RB115b7Rf4fpaybU+VyjeDmoOIbNV3qga+gJgYQNHXBRrcU2heU0CaAjg6ZyQkqklPRuOuIxTuzm+Nrw0HeIwYc8zrtgM1osSPkgPuAgTPk4vEUibP+x/PX2IL/V3+FO771ng83byKXf4uLtFAeG/nT/EuXS4XQYclw5QwjR2OBdC97Sg78dGx6mgqkQFl2nE1y5fYcczXpU9EhU8jUcARtl5WHoECJ6kowVGnvAyW5X6lf4VrtMZ/++Hr+J2GfDThy88mBvq+iJNzbP3q/0rXIcTbsseJ+lwk06PkNcpFGuBJ2nelou36/XpDD28mZj4+/WTsfafKu6+hpWVUJffr3SyUZTuSlN008V+roRmkQmvdhUAX1hVV9uRRAqdGfE2oOwJpRfQzBZjD+ZZ3cRufG4LIUhfmkoUAMcTeOWqaJKtNBM0MkoK1taGNElYdbF/nUNrYUN8rtlTMzWpnFgAbXQEAMfc4fn5wqRwvcValHDh90kVsHmYOxQldw5a77f2+ZWgznHnw2KMkWOEDgU0FGgn0LAmvOoOSc2pzVHZda8tbnGq4myPTEivbLZabrR55ba916mdPOSmCFYKY5rcBjRIC9xVXWsaE4gFXWfc3PHctapdlaxd7gmQuBznm6y3O9gSQI4mbYN+Xv0Zq7ILZVrh/duZHeAV6Q9+7bZ0vYFqRqtOu9HNY7ZIRABrlqnwm4rWf6spVlV/XI32c622XLW1pZvX02oPtWaYdZ1LQseEgRejyFBBR8aZtRmmBT8Oa0bKpA2hXMCY1WczsJ8LCIkyEtBEJ+rz7HPajU9k5vX156diIIpFA4KjG5kUk6Q1EHN9XULzvIK1tAFrhyfOVrU6UCMLt7lSZKMJpU0Vv+cJL/IFFgmIjlA8Sdf4uAA2Aum0ujVFBcl76s+7tCR6h+vRvbZWMeTdJmVte0prfyqa8pM65gLegq3+zvY6m4oOwKMbtq4t06A+5jVaoBZqBRrEMCpNhMMrOVV4QMWKRlZY9VspR4JGLSTWpu0M4NF+V4NuYMOFLO4vXSVhtx8ll9AwJluXn+1H5dGLmoO/VX1spfUQ1nMQLKqSz5dVq4ftDziHat0I8OO9XUnXGbrPvytExgKkt7YZzXxBNp0EEQJpgIhsHmv7vUgVAdm0kN+wuH27g616GyAT4GYDSNLaNzKG1grSAMxfne1LzeQzVficAE1TuULEy1WxwfpkcmPLHA2yf7DH6ilCdq6aUlGCFeTgcmSUxGY+1YUIaEIYJABmAs0B0gvyswV0CqCzGVmrm0034MZCoDFAdwXhYmlQ+7lEHEnxxXjALi740/tP0fvcFQAGnvFq2eNFOeA6nNFRxn0ZfEa74Dqc8Cf3n2PRgG9Pz3AdT7jkEU+8+kxUMGrCXe6RJeA6jbiNu0etsSFm3HRnXMUzmBSfTpeP7PF2YYEo4bbsmvTiV/tXSFRwzL21e4dixzA/w3U4488fvg3A2sYPS4+7yY45UsYQMvqQ8WF33xIGJoGA8cVywKtlj4+HWwDA756e4WHpH1EVyuzt4zPbtXGJ78vK36+f7HX8hgMZebPZy2uBr957ML4rd8Vu42L3Pw0FYXBuOyn6YWlyfyWz4TOCmhF6xXKktfsFAORzUyKFLMG1gfWxKtHkAx9nScQzQ6IaH1RhOBXfK2hhcLbkmBZC98qAQflgJue6t6o5ePIgZRXiACz5Xfw+v4xms/ki7VGEDBzlLdYijKUwzlOHeUqQczQvGFb32wYOuxkLgOFzhnTA/NS6cxX3gjHY+Wdr61MhlGh82krnYbb9+JHUIiy4lqjQULDsc1NerF1IzZ5MV8tE8SQgB8uv2BgdKWVEpwaNY7JZuBdA0yYBqgVF3VfzHCCZEfxcvsl6q4MtnQMAu2j4zJC9bOYi6+OqkEGdqdgMwW+yJiLhX6LA0x37WcNLNEssyxaRrYWDzT2xetvCbow6YyFdhRTI/1P71e1nWGfMtf1J9Y+uMPioSMlaopEFWRlzCehDxj7Oj6zmijJG6RyEpDYnheBeBogygvNjr+MJiwacSt9AUwPZ3HbUhJN0VkEymvVePywGlXfaVDWnN/pPgag0Ok/PS1Omim6MUKtvq3prdW03OkfBnicsajZ5z/pjmycHCC7T6K9rG52AsGjAUXq8WvZ4Oe/wpf4OiQ0pXbnIgU1DlYJ9L9r591IIeX6rb4X368dc0m2q2caX33SQxLphBm9lSBW9iQJVbjx7Jm3BoAasiu/gqCiiq32jd6oAPDIrgJijkP3c96i2N1iFBwV4sgpSknemzuxSswolcj6/BeSq0SJJock+71ZfAPAWrcsW1uZS1oBzSUhcmpGIeLAJLDifehABh35GCoKJFSpwNogFybykVSSDBRKxnj8HRjVhoBocexMgqudJvYquHcQQBFlCm6dis0dS2HyX9ZzV6Fut/RxvE/rySPxC/H22XN3abpbN6C+TSb/Wz1QvlTIFyPRme8dbvcN0XwTI181woH/FJm97WFxgG62Fo70FitZaiPL4iwFae+jRjKC6+ACWcdb74cjgGVg4PCbDezZFC6+ACm/7Utog8bKLXXhWV5+rwUFWTcnGjo9YoVGgA5B2Cy73Iw7djF1cMBVTdvnGxUtcxXMDPVXlpS/KBUTJEcl283xnegJRQhoMQPX19AUWjTiGzgIcGAc2nu7vn5+2GeiiAcfc46ob8fH1Hc5LwuzqOC+nPf7UxWd4Gg2JXMAYeAF7S7rnBYO/f6KEPZtoxlf6Vz5vZiw+7w1Q3PAJr2SPhQJ+7upbNt8tA4oyvtLftrn0qfS4LTurgGnAd07XuJ0G/F8uP8cFTTiEGUUJD6FHnzJiypBAdjMP2WYwxwR5WA3o36+f/CWdIGReO0gt0NpfVKzaiiVYFckAoiD2BQU+PmFFiGtluu0mVmreqJ1hOuooqRhNSIfSdIx1YfB9gAwCvlpMZCLTmqSLPTfdEyQBy0cL6CFi9ykjHxT5AAu2asBKKhY8lYHlWqCdgvZ5NZGHz35rh2efjVYDYC4Bz8sBV92IrstG/ZkTDoMl8sutKbH1T+5ApJhzwKkMSHeMeceIQTAWk4DEhdnVnS5Wxb4QBGHI7m/Lq7NRXywoHqMlH4VQLXjIhXyWOUKKj32AVrBUYYr6nTwCvflnBGBVrstsxlggwpjngJQKYqhJDSEOC6CE5VVvADkhaBacAXTDgl2/YAkmTEKvEuj+Hahs86Wg8/YfZ9hMooKQaqZYM0PRVSqxru0/K+dOAYK3krbnsLaaHY0oHa1aqvV1nXLUAvSmp18vgkpO5wVmEB+12X3RzOClEtBhrkKEJqqBTUZXbfUsAy2thfvb91/HTTrhf9t/t4k81PntqF1D/wYCLsLYuK+AWfJ9mg94vlziG/0XuGRzkzXgU8KijEkiRvfGnXLEnE1VKqnrIoPwUKw1/DQeUZyyI8ooRC34GmiLsQ+TVdVic97reEaijAUBo6Q2ww3QhkjeB6MJDbRg4YAkxVrJUFx143rMdQZNq3UgrfewoZrb3Oh9G/mdWp2sqkuOSreZoXoVZJs8eevWKkAfnbAJ2VTxi5wDqnRqvb8r0jUEMa3jOr91hkGlHvKrZBXWYMDOqubUOl+67iGlh+0XCiAqlgtF2bkn9mKgS0lqoEsvyuCgnyrOgeIuR1g/Kyejs1QVtwp+qtaXQ7c0/1Y+5GbHV5xHS1GwXAvCzgRutvsqk1pVHUwYAjCQU8OcUJVytH83u1Lfx7VwozxZK91nqECblbdfZhfyYI8BvOEX+zHlhwQIYSmW8HQXM3J2T3RY5yJGc/UhZypQsRl/bbtn4dWQpRdofgeCbbnJCJ4dcrYvqn4JlGmtLmtrOG+e3NrH9s+qCtW23EbP8d8HAc4JfLbsEpUXBm8rC9p7NkWpvIKdHvlIkpHqlV021VvaYSTEM2GBWfixC2II/FhrYkHaBCMu44x9nPEknXBfBvyn51/Bly7u8Zcu/ytO0uOhDBjCgj1PuF92OEnX2r034YiBFgQSLP45P5uv8F8fPsDAC0KSBpY4F6PWjCXimDuc5oQ5R+TM6GJBCcWCu0Qcc48+5MaZfb5cInlfP5Cgh9GIFgRc8ohRE54vlxh4wUfpDgMvGKXDqB1O0qPn5VF7fM9zSyAWjTjR+tof9Q+4jB7AS9dUtBq4iwUiVv83L816Pbxf78yKQzb3LsDE/YVMm9cxHOrBirNjmAqZwD8sCHMqqyawO8nklA1EU9irJ0XqsoGmsivdAV6tGVJ59ymjDMD004tVm25mANaGLAYAkJp4Tg1MUZCvYdSfvoBedAhnwnJdDAy18fVubWJxFgSMokdulNL3C/qU21yyto9PuUPigqthwlKMZndxMRpwimx+mXNATAX6bMSwm9FVdaf69mTJAMhmpCJm7l73w9qGNwCqo6X9WFUImBmS1va+1g4BsO7r8MIm09o+roYytYvJdk7iqwiegO6OcP6IwVeTVcwLg7vSOhIAsBQCeVxBtveVGmh9lEi7An1Dqde3OthiZBBZO0Yc4a5ulaZBwWdz0pHB27NR1+dmMiCTi05oJ+0mAPAY0OTQf+kLCrFVr2pzCqib0dc/BON7OTy/toolO5LYN3XpjG6k+0otEEgKkMVvdPY5TMu+CTwHLAvj01OHJx/c46IzAMMuGD+Vofip6xe4TiM+XW7MHMAr15P0eJEPOEnXeLaijHvd4b4M9lFJ8SSe8CcvnmPPM0ZNeBKP2DvIikkwhIw52s2578zDdioBY171i3dhQeTS2r4AmlAFACTOKCAw2AMhN8TwJDYj/hyXCDCebH2dgY2/+3y5xD5M+DDe40U+4HeOH+EmnXGIE17MezzkHpNEMNmcZyxWjc/Z3EjMgcSHZgSEXQHjvTbyu7Q4CETV73MLtLwQSvLNOiqEtracXl155UVsrxGCKU4pEWI07nmdVy5LaGpvNoMNKL5powMoCc4fm7fyI/P62n1hBYoFCBIgX0hDGVfHn0rpkU6g5PsZK0i8K+bKdVKNDhyVjImB3eq9W5wnz6S4iCvgZcwJL0877Ly6rRXu7Jz64K44ItQ498NuRunsvi/CoKE4CMuqfQ0rX7gUWuewAMRHfiGJJTi+p+YcrCKfwspz9qXFM6PWCq5fsq5tZQAIhHxtnuPLNUEHAWeXcqzGEj7HtcrWnOW6W8J8Ccw7gmQyARGPJ3oKwBuOoN7qYMszw+4SQOsnqQLfrODJDeErEMZnoAAAdYI3S8uAqtqUbqraCv1nNvSikmWflE04m2RtJ6tndBQFWsJ6IyvMwk8V6sgHSTZL5iG3LE+iWvZspjawiG6HaypTBJ4CNDLmm4iOC/pgQv6JDDT1U/sXYFLclh0uwojLcMaiEaMkPJQex9I3VakCxlF6PM+XLrW44DKMuPSKdNGAp179MgkCMRJlDGFBHwouuglXacS375/gtEScS4eLMHklqmaF5x+ggph6pyYBaC3tArPjCzD7vJN0OJdkZgJxwShWVX+QHsAkeDmbReCH8R4Ppcen50sARhc65c54wDCSflbGUoIbYFuLTjNvEiFFTBmk27bH+/WTvqhWj5v2rlEEjTbTKtyk675B7lftpvI1eNQEvQYjjSYFmJcIDoKUXOxBBUVDC6oUBXhmOr6oBuvtALVVafFoFVY+YA0c7DiQWgFW3eFtNy/gMV8VsCq3InWrw5CPgJYSkNg8pis9cCoB45TQxfLIy7ZWurXlzGyfX5Ww7839a8kekLvSJBEBskSnsIG/awu/jspS3W8FIHJwFiwoZ+9Y2glqnckmmuHhoHUjycBOrYDyjoB9b+IubrwazvshVFoPiXUgu1cKCYTZf168c4EooCkCpzdri/3YzbN/+2//Lf7yX/7L+MpXvgIiwr/4F/+i/W5ZFvzyL/8y/uyf/bM4HA74yle+gr/5N/8mvvvd7z56jW9+85sgokd/fv3Xf/3HPRSQWPYY+oLz1xbky+LtYAuW5UKQL+yC5BOj+05C+rQDVX/Yg3kn1pmNZrPpMx4bLHDuivnKwr+4JODDArqeUS4E5SBWpdZgrzAiObC2Mgj2+hMDrxLoGAwg4RdYE8Xv1LJXJ3vX16tgLw1Avi7AxyNu9md0IeNcEl4tO9wWaxHvwoILF7TY84yOCk4eUJnMXP3CA2oFTH02X+I272yu6nczk2CgbDxbMoP3qUQcS4dTNq3kLIysjD5m7DoLyAVmMF0BTBdhxHU84Uk84oN4j+twxiWPXs0mLBqbhd4n4zX+3Ys/gU+nKzxLx402stn9fbpc4fly2ZDNR+lxESZ88+IFDnHCuSR8aXeHP3H5BTrOmCXg04dLfH48YM4BD8cB8ycH9xm1jobZfBHkvVrjH+r647RvADDnF289VgGbcuFgp+qzmsT+VApeZugxQsZg5hW+8crC0ClgycFwFMGpNeozvsw2F1zWQKvnADnHdTY7eQJYrHWq59g026cPCsaPZB2LVWDV2WQJyYUgtkDN7hUj3tpckRgInQtldGJFQxXlUML40OF07FH82KoLF2B4hxDEqD9LxP3DDvcPO5wXw2tkdwOaZ5NxjA60UiX7vWsPixLGY4fZkbsVsV0ZHDqae1EtlLaaBWUKJrPq+zJNJujRONJ+zsKraD/3qFYBUxVp3PZZhbeuCaX6WHcCmQLmux7TOaFkRrkQTE8FD18H5mu3avXZvO3LBNmJUbveYP3YwfZ4POLP/bk/h3/yT/7J9/3udDrht37rt/D3//7fx2/91m/hn//zf47//J//M/7KX/kr3/fYf/AP/gE++eST9ufv/J2/8+MeiuGeismExcvFVF3UqsA2P+3UMpTF5qE8rRJsFSEMl0psfxwxWE0MiFewU0UghlRMl3NrywU05CCAxqmtrwk13i5lMn3SZlbtrx/FMumtzZ5itaVyHvFuN6OPFihrwBtdMKJSah6JWoAwSnJ1KBOKsD92E2QPdmbKbpdElW8M9PjzVYP47b8BPHqctJt2PZaBFgy8YKB5lYP04F4FM2YJeDXuWju6VsDVx7Y6kVQwlIlmCJ52RyTXiL4IU1OPEiVMOWApwVpDmRHO6/dfKxaV90YEf9jrj9O+AaCJ4DTRe8DUixTN/7px8NfLfa0KgVblVHBlKdyEH5ruLmyPMnxAve503RMAq6oLtfscgkdykrorNm5qFTba89roq1XqMAyLS742c4PgtLfKdthwa5FXbmldApOLZQ+2tQo08X5GLgG51KTDnbN09bYVXcUfKkhVq/sPsIpauKJe23tfE/Sguj+7QQHgoLX6ukDb87n4z7diQrqeY6vwN9+DwkFW3mUolnzJEqwT0Fnhky+Mo9xonf7da7E9G+m1GPBD1o/dRv7FX/xF/OIv/uIP/N319TX+9b/+149+9o//8T/GX/yLfxHf/va38Y1vfKP9/PLyEl/+8pff6D2nacI0rajZu7s7+59nE1Rt3hhiQUkGmU8vI8KJMH1QoEkRJms9nL9a7IZymyyOlrEZUsm/ADdk5juGDDBgwimC76ORyDsBDWpZysLgs4EcNADTE9NV1kwGCkiKeBuNJvRkE5j9y63zkqqJ3JxGahCoN7sCiDC5t2ByYq/iAFHC1y9e4sqrukUDPkj3phTlgKJAgoFspjs40OheBpykx3Uw4Yqn6Yi7POA/3X8VXx1e4aPu3lrBAI7St1lr5IIDzzjEGVfdiDGbstOr84A5R+CJHf63Tk/RcWlt35oEAMBVGDHQgk+X60YQB8z95zJN+PKz7+AmnR59//W5FugZPZkBw0MZ2mtUEFXl3s7FOLo3uxFFCaepQ+oz5g8YqBqxZGbcy5Ehp/el7R/m+qPYN4AfvnfIHBBvMiQxcvTrsAa9gmYeIqNvkbVlC9uEmRV5Mt9Z3hkwaj4lLCEiXZemjSyZTUSltqujPsKOVJoPCUGTIFwuZgwwc8NyaIPPYx0rRQUcfPVoDurc0PEDAyXpGJqpvVXg7OI/aPtMOCw2e/ZjEhDulx4vpz2Kknet7Jj3h6mZFhQlLEsAs6Lr3NRkiY6NcDMGrrNrRX85tSCbjwn8YDKTYLi8pJpMZmCI/5u7giJmXaqkoGDzabCu5vNuf7h8sKA6K9XWcjkHFAomMJQZ8bNk0o4f+d7rsYDq6EAJWFwxasjmGz67q9CZkENAiQrcRYSZUJ4tCLs3G0H9oafzt7e3ICLc3Nw8+vmv//qv49mzZ/gLf+Ev4B/+w3+InH/4Af/ar/0arq+v25+vf/3rANAg4QDWIXt43SsSa4bYWbDkKO25VDPYehHXzO91Kki92Leyi/4+WtGL9b3hGdaP2L9X0fLND2uWXbO9msXW4/F5Rp2vzMUoNQLCJ+M1nk8X7aUWDZg1YtaAReMqwQaTTRw1YvFBt7WUzXi+zmrrn5N0Zgzg/rO1ao1ViMIrYVNyUg/02oKsuEZy8JPBkNaarkHUdJRNaeomnQwI5TPeaVNtTxKb9nKVfbTPZO3rrMEoRWDMYi2uPuZVnpLNxvBR5isAnQP49Nh/9/36o13/I/YN4IfvHbWiAfDoHlS/n9u9V2k/ula7tK0K1a4rDh6Mt/TCbcUGtPZopZ+ZAA/svq/sPqqVJx7vSVuKiwOHeDOPrDPk+lm0N35tk5etFV2tHmm1CKzV61ZLXBw0VVet1mM1IKF1/+TN+WiSjZsKv9F6tkVr3ZfbvLUWFrb/ycKPOwEEU8caaW3x+2u3ijeJI6zlkSlEew8FuACcjQf8fVTQRxdB/dz2PTQaVe1C1rl77Ta8wfpDBUiN44hf/uVfxl//638dV1dX7ed/9+/+Xfzcz/0cnj59in/37/4dfuVXfgWffPIJ/tE/+kc/8HV+5Vd+BX/v7/299u+7uzt8/etfh4j5q4owltHFrvuC/CGQ600isHmqt1nIaTjitA8i+5K0tmyDAGzzXrDZNVEnwIcTMEaz1MoEJCOD60A4XdUvc31PEgLNjHyTmy4pMoML4Cj3NkMgshuKRkYYCbnA5jONI6ZuuiDtOTkHnKYOr+YdHpYe/8e3v4IQBd/43144dSZh4oRJEj5drnCXB1zFEYNLOSYqKMEC4cfpJfY8t6rwVDrcl6EF31ki7uYdZgk452TArJhxdr7t0/0Zfci4iSdcxxN+9vI7EBBO0mHPMz6Od5DX8rqn8QE9L3iZD1aR9w9mXBBGjGJUoEkisgR82Fm1/sn5GnMJmCTgIs74UncHhilanZeEl7Nl4okEnx8vMOeAj6/u7Bqp1J+gKKmiQwEUwuH3Aujl+zbyH5f1P2rfAH743kF1M58C0suAslfIvkAP2Zgi0Uw/eDTgkgAWaNNaCcU+QztCTA4AcoxG7VjJ4m1TAniXEVPBMkZHz/oBefAMI0HZWrQgdaENWDCp1nS18p4JsiPA+bvifNQtsLN175JAMkFO0Xj8k+9tETYnBUCHDFVpXHTAkucUCk5LwrhEXA4TEgsmiibK4eCo/jAiO/fUeOuefLO09rOZJzCmOZifbVDwPpsJwTkYR7gyMnqfy95HSDIxDmIFhoLh9yJ2nyte/Bwh7RbkMa2m8WSKXURuLiCyWhFuzksZrIUfXkSTrxwEKs5WaZ1FC9RavOugxoOWC21jR73INlKPAt3YGf6o9YcWbJdlwV/7a38Nqop/+k//6aPfbS/+n/3Zn0XXdfjbf/tv49d+7dfQ9/33vVbf9z/w5w1hpx442SpL+1sBt9yjKhhVAyJ5P6ZqZ7qUV7Vv2t4I6rGOAtpsoH55tZIG0crzYiujG2E+WSUt7r4h0cBUjS5UF1mAlQhDTm95wF4l6+amKqlAImEqEZnMdD4l0xdOulaNo0ZXcDJzdSmExEZgN3GLtfyuc87tSmRo786ddgrbOT/n1BCJDEV0cNQica1MS3j8OoApVYlVowPNSDSgkN2oC1Zxi0QFE2IL2gGCISzo2NDXkUzIola3s0Q8LD2GsEC4ODLUjOSXEjAv0TRbvQJoH1PNCQrD911e79cfwfofuW8AP2LvSA7XJYUGrO4/XtW28U6VAnytuqwz/jabdS4nkbph+qYz9aii885Vze2y7TcS/X0rSGr7ngQQbI9SoDmFyRxaAaGL8z6rKMQPOhl+LFTczMA7fpKp3dcAGlCKoeusVhgEQyHbZ7VNtbg2wZa+U1HHtcpl35crylf88RUMVX3H25zcqVj1XNd2t/SKvKt7LFqruNqeqn+lwDoTrnr16vsoz/6c4N8DqX8HvPJyKzq5rPRAMFbENND2ZJmCfQ9vsP5Qgm29Yb71rW/h3/ybf/MoO/1B6y/9pb+EnDP++3//7/jTf/pPv/H76DkANyvRWauiSG2vZHKBa6BKccFVUkTIUMjJrJcY0gKtZjYObVhnISrqxgSEMphWaoOUA2tVS9bi4K40KTdVM5hGgBkcEFaFK8Cg7lFQDhmlXykpHMWCq9+AogBmBo+MnAq0X3A7DuhCwZ/9ynexjzMeSm/iDukOkyTclwF7nvEkHptN3teGlxh4aepRd7LDqPFRoE1kx/k0HhtC+VySoZ/nPT47Xri4P5ATt9/X6jQBmHx2LGAMNOHAEz7PV7gvO3wpvcIVLxAw7ssO351uvFV9wNPuiI+7V3ZsSng+XUBA+OnDF63dXb1qAWCRhNt5wIvzHh0X7OOMm+GMqURMOeJ+7DHe9aBg1YjUTdDvnfHjArl+7/rzR73+Z+0bANBdTyiUgKTITzIasrUmYzUY7ey6oM2cVTJDFnIRBBOsUPhYixTTlKAKxK6gZIZIaO3HSjMhn3HibJGzXBn/k46htUUlZqcZecyppgVRoGMAbpMZCxwW8ENAfCBTlEqw/RCA1MwyGe1QvDKmKUD2AgSBniMWWe/9WWwvqJzaUhjTErGwYDx3UADDsECEME8JHCzRZ7ZRUr2TlsWC0G4/oRTTaZdsyO3K1KDB9hlq/OHajkZrdVd8zfRRwXJpvF0VbpaElZ4lc7A2MlylyjsXUFigzIT+hZvS3Pj3yQA/BIQTYfkwg4cCeUgm1Xk0t6JyMLR3dNtDBVDuOjuPmUCnPyJt5HrD/M7v/A5+4zd+A8+ePfsDn/Pbv/3bYGZ89NFHP96bJUHJybhaDWHqlStZxkPsvFUCaLQvoFSXBveHrRkiAOg5NpCE8nqTmZg1GipNp2Bgq3qDsM1J7MH2+GrLp5uYjJZ5sg/5LTWU2WkBm1lDEyf390E2QQ0N9vtS2Ej3ADrnxt0uO4gSnniQrGCpOjsVzrgMI/Y8YdaA5/kK//H2p3CZRny5v2uVYl2mwGSVaJaAT09XeH7a4+XLC/S7BRe7qbWePpsu8WrZAQAGXppwxu/PT/FRusOBp8bnPUmPEwyANWo0swJ/zz3PCFAMvEAC4ZiNllCr3/oedzz462VEFgwx2/H6bGkRxYvzgCUHN452pZrteYaasPybdYLerz+k9T9134Ddn9wpBGbRuSbLsKrNL4gKwlFHqtLkwhHJpBWLWpBtXSFvmxIZArgm2jK7kIraPtK8XhsjgVp365HpuVpFCDF6DMj3jDor9GOjTOBMKJU6U6s+Ce11ABhupeJCKgDTR1yVaWAt4cf7AJGCCYipNMoTYMDU4OIe8xyRc/CZ7jpHJpgohd52qy2hH5MCzdj+kfkCoxVN9fyWTloxKt6ebwYSdWZczHe3FigNac4AomK+WjdjKoDOpo9dBqxYDlIbJXZ2HBpqASfGyxVyBydAO4VsuoM/av3Ywfbh4QH/5b/8l/bv3/3d38Vv//Zv4+nTp/j444/xV//qX8Vv/dZv4V/9q3+FUgq+973vAQCePn2Kruvwm7/5m/gP/+E/4Bd+4RdweXmJ3/zN38Qv/dIv4W/8jb+BJ0+e/FjHEoYCmQabhU7rxSHOoTSxCzVidAHiAxsSLZglFfcFMgarZAcjeIej266xnUhOAhWYuUEyGUUaA+AuF1QIw2cBZVAsX8utnayFIaj9a6wD9cUzzWgiGTwoyhSAqmASViQdsgVk7otlbaMHBddHzTlAOqPR9CGDofh0vMSUIr7c3SFxbtrDJihhQelpfMBAC+5kh/92/hD/4Xe/iY8/uMVPfeUFFgQToHA1mQpuiiyYJOI7t9c4vtyh+17C+DHj+nBuFnfffbi2jJgU1+mM/2X3CZ7nS/z/jh+BD4qvphcmD8mC7y5PWssYAK7iiFDFOTxBuAgjel7w+XyJuRgwSoTwyfm6edvedGd8PNxiCAuu+hFDsIBbAVwPDwOgJiBeckCZQ1OlaQH4dUGB9+t/+PrjtG8ABgDqUkamYHPSquy0pfIR1vv/HMHngP45Y7lQ5JsCVYYGMjRykNXXlRgcC7rko5fMwCmCT4xyaVxXwANuXx6rzXW6ApnI26FeTMQ7M0XAvlbiMK7nEpAyXG/dgkPlhDZwaOXhdmomB041JELTFBZv+2YJj4zk67EGFuz6GVkY42iazn2/IJAiBsHxfoDediiuTZD63DiueQkYPg3IO8VyU+ygxNpLqtTa6Q2sWpWwgvFkQxTokCHJ91ZXCqwJczvcxUeK1WowoqG6EYH5I4AWRnxgcCbgzJBBoPtiHYN63oNC97p2SmNVysJK+YlA7AvU9dj/oPVjB9v/+B//I37hF36h/bvOUf7W3/pb+NVf/VX8y3/5LwEAf/7P//lHz/uN3/gN/PzP/zz6vsc/+2f/DL/6q7+KaZrw0z/90/ilX/qlR/OYN13WPnYAQ29i3DzT2lKOAmVyAWKg8EaubOHVPJlNpxQKE/KOPtPxgbsSrfMXpVXc2lvM0vnvHuIqZFEIqgw6BpOBuygNbUeKhkIsU1izzDpjUNj1464kvM9GRE9OB+jWoFwFvacSwT4vGkvEZ8slruMZT+IRi0RMGo1jS2azBwAdZXy5v8XPfPw5phLx//jun8FPX73AN/dfYB/mxmV9kAGfjFd4WHpc78/WEpoY0b081Sk5tcI9l4RdWBraOTky+b7snD+bXcGKcJv3AKyaFecDj0hNAWug7CYLVlkfS4ffv73Grlvwv9x8hsgFk0QkElzECa/mnSUKziGOydR85jFBZzZbxk5A/SYb9cTn/frDW3+c9g0AKMeEsnfx+WAUsCY+k4Px4FkbILFKIo5fcu3ztFaXVbxi5aMSkAPEvWs5KEpfUMjappzEfVPJBHaCOo/W3zNH8MQQ3uw9wdqZympJ+MavFWpSjtLZ/sdzsH2sVsqvd22iWvev7jedtgQgq+0fqoSsjPOcME8RyROHcU4m5CGmb0BA47NzUJSL3MZrJQdI4dZJHD/0lrwSlMXa4hWMRB58PemorIEtEtuEMDb2qc3NZ+0otsVq5gH1derv/Zzkw9r9bI5v1aChttRrqztYdU1klnp0jMC+NLu+N83Tf+xg+/M///NNcvAHrR/1OwD4uZ/7Ofz7f//vf9y3/SHvZa0TDX6x5LBKrgmZaAXUqlAYj63BwZ0AXYMqJnN5sP6/OppP2rAfsNYQ2Krb6mdpAdreJhwZ0itkV5pQRnxgxDPhvPMvvZ4ehQd9WsFQNeP039NMQGetGgVQgllExT5DK/qvtn7UdIaLMmaJeDHvkajgg/iARc1B5zqcsQ8r5zBRwUfpDv/Xp9/G//7ip/Ctb3+A9A3BN/dftAqzzn1fTAdkYVz3o+moLgH98FhPmMj4x3MxT8xVjUohIBylx8ALOiqOio74TFb6EZQxusDGJBE9ZVynM67iCCbFsfQ45g53DzuUPeOD/gFZGGfpjANMiu8er3E/dbjsZ7MRTKWp0NDIiEe2cfmurPSNH4OY/n79/7f+OO0bAMDn0DSMTVzG+ayT7SGaykYkwveUJIhPJhNrqCAmWOIswojJLBvLEu32l9pStuCh7EpOQSzJzoz0QCgdAU/m9lqqAM8E6Xx0lMQDcm7jJFTgp+8zeigoByB9LxmjYQ83RcEK0vKthVMBMVBOsUklclq57JMHW1Hj0coYkAczXZ/nuKHkUEvwcw4IsbQK38Zo9qZ1nEZPZuvQnYOzK2xfgxqaWMVV9kBO30Fz6rIX0NXLdgtkrfzYbb5c99QqEFQX2eN1g/Zuf8vm3/665KO+RmOaGeGBkffF9uUfY9t4q7WR43d64IogPax/HszOCcCKJqv81EacqvMAv8HrHKb25uscQGyuWordcI0o7QLftRIFYE4b8Iytqc7Y++ULgfSvtaeAZpVFM6+euJUzVg/X/0gNwF59lcWySGZBigWJBXfzACbFLhpit3Jiq8rSwAuu4wkDLbgtBwBoJgUfd7f4vz39Fj4cHnCZRpxLaiCkuzxgkoirNGIsES+nPSILri9NeGIpjBfnPYgUX7t8hSFk5I35AICVUiQ9kIFEGb8/P8V9GXAu1kp+QQccc49vn9aWoBnVZ7zMexxzj8QFhzjjg5sHXPdGYwIDvWR8sRxwzB0+2D3g6UA4Lj3OOWGeQ6NTaCdmpBIUOAfwvXUd5MMFHN8DpN6lJUkQyUQJqzsXJ5Psa5KJmcxntVjSXPYALv0FdEXQajagoGq0WW00Q/Xz/QAK0oCSWz4mdwXKaoL4QbdjYqAT5EsrBuCCPBXfoYBVf4DZ/NXH7As4FUiyzD9fl1XCsRgNUQnmbBTJRG82IjtbBPMuLlgkYMrROLRJMI0JMyUL7gSkzu/psWtWgnavhaYxX07R9jQ/h/QQwa4pXxTIikalsg+07n/N+hL2/8UVqupsmzaaBvA2NI1s+3rQVfN+Ezu1MPghWKu9F2uj96UlVM0MogZtsffWJUKit7srYIrU1LSOCfLwZtfc2x1sHwjlYpORENBEiQRuFk9ri1CxZjyAfWmuDiLDJtDW6lf1kUxjkxfj9T0AAIM0oEJDNfr7aaemOLLBG2jNMhWWMVePynqMm9zALrxKM7AnayFoKGBaxc+nEhFZsI9zA2vUWS1gMP7kFeXzfImijJ5tQrvnCd8cnuPj7hbP8wVu885dcxTH3GNRRh8yBCu/7mqYMOaIaYmYHCyxjwtu0hkv5n1z8wFMeQqAi2T0YLJqub42YIIVd7nHi/O+8f2OQ49T7N3ez0XSSXAznHHVjaucYyh4lffIrkIVSTB6wiBuUN0oHSxuwciIJ1OFWZ6+3md7v37i1xakVHidyfmvK24DHbnYDFaZz7rI9gVx6UUlAM4jVZCBbxIQqlrcZudnVkgUc7nZUIrsl96mPnuVHdcxVhPCwDqbreL8FGxM1pSRYuXn8gq62uxDtU1eVxOsca9aO05pACbxBIPCKuG4zAFExYT9JUEWRui8I+izZ43kuBoHchVAFoImdt/g0vi47VQUQ24pV1vC9dzZaO+179NpPdLpqk9QK966FODFaJnF6VPcHJfqY3Vtr9fuhasMSh0beBdMMoNmZ668wXqrg+34kSB8PELnAL6PoGzqIKUHEB2MBNjctmVBugmGduIleUB+vd3g556jeTEuFawg9sVU1SG5zutrVt7bOYLPVrU2zi02MxReLwRayObKm5uoLV4FOHR0yHy0NpRQQD4EaCgYswXbD4cHE+AfL621TOZdO/DiSlABz5cLMCm+1n2Bjkpz/xmr2bpvOaKEL/V3WDTg0+kSDMUHuwfMYpSasxrX9mo3Yp8Wp/lQE6ioxu9P4gmBzNHnebnAogHHsgqfA8Ax98gScNFNGHPCce7wxbRH4oJj7jFLwCl3ECXso0lGViBVgOLD7r75cGYJOC0d5hKwd9pBzpZ1lzFYgjUS5hsBngJ8CtDTD+Zpvl8/ocu7WLIEYGRo58BKrx75bMh/M3UXLE+KYzuscuP0OoQIjmwlxIsZROu8sCV88DxayLotm+pNltC0eev+wCMjzMC8w5ocbNrBwGt7hRKkF+OQKpr2AMiSfnsjY1LkQuAooADIMRnwpwZb57gvwo6qVpBrsdeW8DJHECv6wXx45zki33WItwH5wwVp51r1MyN+2kGD05v8GNAZPVLmx4YMGhVUCPG5ySrmw2pBytG6eXmJK0gJnjTA7PCsakXrOlLUNgtHEhMZagGUIH4eLFngtcYRgozBjsstUysaHEFBD8Za0ZsF3L8ZQOrNQvIf06W9oBuy9dSryW/LDu0vUqzSiV4xPpINc4h5k0jbtCpamkWmP/r6ogLn8NbX0tU4WTwT3rQkqrapttf1v8TF8RVrkPfjUdbHot3FZzZ+MRUhLMJYHPJeVxHGw9Lj+XSBs6dx1Sv2dTOBSqtZK9F1+NFzRl/b0rDWMkMbWpFIkViwiza/XZxqUMFSgaSJT0wbh5/yWmpaj6cL6yxVlNuxARZEAWAIGR3njVSkoZgvwoQAC/jk1XEfC/qUkVzlp5439Q1Ie0EYCfH+rb4V3q8fd9W5X131Hqu/q3/Ve7v6XjsokV5/rXptbV9jK+tY6TveDq2ayPZYNAwHbasp4PsruO/7Ado+ot65MxAotTbolr/a9qHahSN/z7xKsdZ7twpVsLfCQzSPWcm1Y2Sdte3eWM+ZPddfX+wPkvofacb167mxv8krSuskrMe6pQZp/V7q3r3pDDSIjWIFUNW/fHaOLWhsI71YF9fg7M+lGh/ad4C12+G0pzdZb3VlS7uMGIE5WGYkyU6KHAqoK5AQrc2yUDN8106BoYDgPfromWCFwZ+DSX+5uLQ62KpU5PJm7tJWDeAV1dZcf+yGpgLQyHY/Rhgnl+15yrrOKdrsFnbze7XNUUzQQgPoRAgTYfloQX+YMc4J45wgQlg6a/VGFtz0Z3x+PuC/fvYB/szHn+DZ9RHfGp9hKhFPuyP2YcZJetyDH5m873nGRRjx2XyFc+kQ6GQqTjlhLAlTiRhzxGnqwCzYd0a5uUojTrnDgxKYdrhMEz6+uG2IY3Ps6XAVz7hIE75YDpgkPtZb5oKOMw7J/v2kP+FZOpq9n0Rcxgl9yHiazEDhZd5jH2Zch7PJTxLj03yF+9zjuhtxSDOmErGUgPvJDByodhsupfERD79HiJ+/RyO/S4uSQNSqM+yLz+bYAEnF7C4VaPNRbAMDWbepLvY9pFadVV2K43pN6RgQjoxy43PKY3Bgk1d7nmBrsMoOxRgMhdc9QabHlRay72uABdbMVk0KjJ4IfJ8tH2XazDrtfcODCfkXWdvIADC7PV70hLUIY/69g3UPvzSB2YQvWJ2zfDMi76K3Zq2NDiEszzKqQQCwHaPRozk0LYTupbWW84VCBkG4yCjHCL6LkCuAdurFBkBdcZSwIi8CDWGl+ozBZC1TFQda92QCoI7F0cm5GaTtMdS5I5pXxTEVSFDjMM/WOtZdQQkKzAH5vFIYf9R6q4OtLgyiYnOTpn+MdTBOakFtI7UI1HmAL39cnYW067Chgsl4duTP8SDZqtD6+JpVqWWwpH5R+zGpH8MqWuEVt7eyW2s56CrQUcnU2w9dX4ssU8vZCPkxGfb31bRDF0yOkYCWdW2ryX2Y0VM2eUU3G2CoVaGo9nqrmcAiwUT+ZaX3mEyjZbaRChIXzF55RjaeK5NgceP3Njt27u4uLI5kDM3OCwLs42xi56TtMZELBIRdWBC5NH3nemwL2/8LDJWdhdGFjOjIykcSlPVGjysHuuwA7H9AxfB+vTurViuzWdOVnaycz9rlqvcoNvsD0IwJ1F/HHG/QqufmnxoBuCZzM0BRWitjBpoKBPx962Najr9WWdSEHdAUo6xLt+mo1eKg8Vixds7q5yBL/msbmeGmA0FMOWqOzRVIK7B0s0QJS/b7OznSuhCa7R9t30tdFavOSjf3HRuzQwnN2Ucq57h+R/VceNXdEMpBrdhyuo7xitGq4nYuFOucOhN45lbsq3OTNcpjdcD6Prx+xw2k9cPMDH7AequDbbiNwNcLYiyYDvnRjbFmMjCjdrWZCgAzaq6w8DpjlfVEA/D+PFr1I+InPEhrzUiqNwvsufWCrq0g8swyKND7F+UOIjSTe2kCZafA4K0VVkh2g+VOWuZWlwli27wjZ8bicm/Xl2cEFnz7xRP0KeOr17d4ujvhg90R+7jgi+WAQIo+TvggPiBRNhUn6XCbd43qcxEm9O4lK0y4zTvMEnHOPn/tTwD2uB97BFYL7H5812kEk+AmnVtAvC8Dns8X6DhjF5YG0tqHCaKMe7fJeyg9QpgacrnA3YLcDSiR4BCndpxF2Waz6EyQwNe5JMwS8aw/oijhe8crzO69SRXc0AlC55sCgPs/maFffl/Zvkurut2UWoH5LZZuGelIOH5TwIfcDM5l4RYotG7gvCbp2/te1LAVnMTddhi0K6BDBn/aI4yE+cNsFersVJdkwUXJ9inadtFq8u3tT9v0XYA/2jVNCwMToIdKWbJgx4cMOUfElwFlL9BDaYYJTWd9b8b0zfITwEUyZbgXtwfIFz3Oz8iofk9mlJos+JrmiOm+bxK1+sroR/KNEanLmM7JugaTVd5pbwIzkmkV2CADdy3PpPFsdWHgPtn26l3Ldq63sZDNpKVcFiB6JcsK7QkYAzBF6CFbN7MGbyHEh4D+C8J8Q8gXgniy8567guBmJc2hCVjjy2aZgcIP6Hb+gPVWB1vpTItTleyiDR5AR0Px1ZlnXbTJQhSwTTp4RlclzNrMBWtmBrQszBRX2DM3tNkMABPYcBcKaxFv3qw+lux9qRjdQOo3UAjNt7IerxO6m0TYJuhqIRSElkFXHhiz8d6+e3eFq2HCB7sHiBLOJeEqrsGsLoa2n22t9Wrbt+oh18dWObecA+6XiPvTAH5ilXAkQeSCqzjajNYN7QETtqiiGqWm0v6eU9ViJZsRCwistYJeuxBZjKJ1ks4qWjXB9yzB/WzX45uKndjIYk5Bc7RRAPB4FCBAODH0+H5m+y4tIldMqqhTv9+lA7Kg3dPehFo1etnbrV4J11wbwLp3ZIvAzR91s7R2pmqgfnRQaKYoWvEjzdxk+zgPlt0GfFmrVd+nNAmqwhRYUXb2+DorJYIZcwhWdan6MRybMYQFfb/gNCSUhXHKfStYyKkwRdioPz52EzWtAhFDMjPL+iH9nJVcxUTUBCq2XUJeC6CqTd9+Xosocd6zI5YL2JzYfE/W1875o/MmKzJbyTUSyGJD8wQGmna+skLKCnBD0Oa9q0KmWDX+ERoR/M9aepHRp4yH44B4F+yCGgrSq4D0QJivFWUwEAy2ICSgmQao03JWH1lYRepD8dAZKKCqi6gCNLPx1Tpv81b1Jxf5DicTt6gQcbPJKhvVJ5eETH5s/pqq2BjMr2TuMr8W3NWOR7PNfzga/SeQYtctOI4dHj4/YHp2wkf7e8wSMJaIp90JF2HyYOfqTpxxCbO1e5Aek0f/Y+lxtwymyFRCay2NJWHMEfMcUe4T+BjwPW/7MsyW68POAvypdEYhgqLnxYQrAJxK3yrbh9K3VvLWXEDI1KTME9dOxFk6sCgmNuu9WaK3uBmXccIumJRccRUtwNrcqoTp2K1GEXU5+KL/gkGv3reR36nFa4VqXHcBApAvC8qeTKWtdixr1coEDmJiFcAKYqqvWQFOQqZKtpnZ1mpMo6IoVqU5raXxelzVXJ4WCwx6MIGdpnBEdt+rc2hRaB1T1a6aGyholYG8mZ2bbxq/VQ2pSlTSRkGtcuyHkPHkcAYRcPz0AD6zfy41ez8AuTBSLDgMMx7OPeYxQoeC0hH6Lht4qrZ+vd1dxmBVsAvO6Cahrt29So3SjhoSWRYzZTFzGQNqqXLTOOaRTae4w+Mkh9BQ2Q2I5cE1XwASACqADPbZCFbM0MSu3bC2sbkrQA/Tsi/GSKGHdyDY1r56TAXTQVomWfYKjVb5VulEwOYADZlcM8Ft9alYK+KdySvK4ig4VgNLNCkvrDPVyqGr9wzj+1oOdcZT29WND+bBVaHA4uRzn1eUc7BEwDU7abEbfhXfABAsOx/nBCLFeepQMlsLmi04RiqILI3S88l888g55zqaQMUkEQ+lxxfLAbMH3UqneTnuzGaLFMepswyzE0hQPDmc8fH+1iUbBWenGPWcMUvEfe7Rh4wrHX0+y3i+XEKUHr1PgOBl3ptxNRg9m8n8vQ6mSOWI6aqW1buAxphTq94jCy67EQ9Lj6Lc+IItafI2fjmbHjUtjLw3EYL3691ZRNZGBcGkEltA9W6YwqqlKiMIi4lS2LWKHaSjBB08kU5eidVZag0yHlCU9VEFuQVcal7b1MS2fym8SKjVq3dmtO5p1fu2fagf8EG9aueNClKeYwvC1NvslIIgbNDTotSwFKUwaJ8hidfPBqsgq7NPDC7sw0DwQM+VSeHVdptBs5o13Sn+4Lk4rLLUzFY5CqOImxpEK1C0skYW62oSAO294q+o8G1DoM7Gk1qh5OdfBKvFojNIml2rJz0yxkcVd1WVUiJo5BWE9gestz7YVrTcuC+NRC27AjlgBQXIeqLVyelawVQAKl6cxOQfJZr4v6px0qo+pjqAAgHtxiEHILVZAux3LbGqfztloD3GAyo8kzNubodwZuTewBl0jIZWvjJZM1osg6Xaoma0C2ucnd5ztqDLnc1SzznhEBVMpckmfjZdYioRfTA5xGpn13PCi/mAL6YDhrggkqALxSrQsUdxuP+yBKgQQm/z8q9c3OJrwysUGDjp1bLHQmZQv0jAw9LjMk7N4GDRgLs8NCpPZHPuqc81QQ7Gh90DhrhgKhHnkqx9LQH3i6lJfby/syCbE0bXhn7an5C44IvxgLmYxByR8aSZCRIJ5RQbWpEEyAeFvCF8//36yVjklS0FBQ8ZZYzARKvqUr1fgU0blDwIOObCq0jtYXuEz/ka5aSK7bS/N8HcX6/1qRey3dg3dQ4CZR8fefAn5+BqlWucyeQYw2bzee14LegoOKwKaTq6ZOLNjJAsCa3OOtuVhZGLmX/0e6P2Tee0Jh8CFLVRlsTSgnnqsgGq6oivFShrJ1DPAfE+IF8WwIU9qFagikaNoswGyBLdCHV4d29mIJOhqZOiXOc1ydnQPZVWkCmnYshxNVtEUWrtapoZtNjnUkLztq0VLjoL8gzTSlYyxPIjrvOPWG91sNWyXgwggCbXvr0Qa896xkQOiKrgAWXv+y/U6DYqnsUArULWzEYV6RTKpbWJ6uBcE2zOCqBaZ6HSehoizl43vIo2r7gsawanBIzBZgVRQWygK5oNsVgND9R5tU0Qg9AqdIVdlBOwBu1CkCngCOAzAB9f3eGqO+NYrE18zAZV/yidceGuQJMkPBSrQD8cHvDFtMddGTAEu8n2/YwijFyM6C7CiLEgxoo8VjAKUiiIbPplAy+OLLZA9r3pCldxxD7MmCSaW0hNAryaBRyxDMFd3rVjilzwrYenpnwVsglbhNkBUcHpCoKxRMwScHseMDvQrBRGng3wRt7KomyoUxJYZfteG/mdWioE3plGMAGbexJrsAQam4D6YgHgldvEbVThKKoDG3mDAvbniv9j28b0qkyxqeoU5r4zRwsqXWnerPW1eSKvxgy7UMdY8Kqs2QSqJxOZwCeG7AAc1o9EfbE4T46cDhbcgZWfX4QxS0ARM3+vgZODtsqfgqJzANTt82vb76Ks1bEQcvbArrB7TGBGD1GRn2ZUUxja5ahplTEAANjJSURBVAY0kszgV8k/o7TvROfXsCuER+ePzgE6CMI+t5Zz08AvtDYbyqZDWYMlmRmJVbxk5vWebFU6Ft1FyL5A9maZiEwIR4ae3gzv8XYHWzHNTPUWAWVCOBHyzk+kI4nNesrEron9HM4149LW9lVWc/wJ2sjVvBDEQVSktjkb4GmtVLX+DFi//Hr+PYsNo23wsqfHkpKLz4u2LejsIuM7M1bWOofZfqd+c1U0pM7GT+Ou2AfMjDIFjCFhkYBEJuk4ISILm7Qjzxh4wSQJoyRkCYhU0MWMz8cLnHNqnLs+FORK+xFx8IM2Cy0A7iikDUXMsNlL6gpeLXu8Wna4CFN7DLDqJr8utAEAkwRk6fC0OyGyIZCXElz/2XxxGdooSYy1LT0tEfNk1b6qeQNX0EWtNkhh3ye9eXb6fv2ELIWZvfsyj3VdW7/tF/ZgjoKyMPhsNp3oV3ASOdhplY3VzWtiDeRNcQH+HmvVCngB4P6qFtikdWaUteFKKHjgigaCaq5Fsnl9X7wQNK0/q9rN4vcf1JJbZk94vVNUhDEXp/tVH1eF023QgleKBefcI90yyqCQnSW3HMQRx2zdwJqgqHUQdSgIQzH95IyWCKvjKMJIkAhTAxQPmPW81Q4AWdVTwWQ8A6UDOBSjDLGC1JHmavGCKoisCgxVUYza4m7f/+Y68O+WJ4J27hbns2NeCPrYj+WHrrc62MZ+RdYSAdILlktqtlOtlQC0SlILbPZKMEpQveF8dqAef/Vk89LyJLcvRx2t+Ahkpfa6NDO6F2ZtJb1aMPf5KiXBcqGg8li6kWdGfCBQiTag74yLVy6kXZjeB1kzMaC1lKiQE68BOrkxdYnQnaB/dn4Ez1/UMtasARcuDrFowMtljxfLAdHRwiYyAVx1Z0Qu+N1XT02ScZigAMYlur1WzV4Zd8uAT6cr+0wk+LAzp6E6Q93zjJ4X7EL0Ywk4S2e2gEkRHFGYNeCYO7yad3g57nDdj7jqRnz79ASihOvuDHaQlsC0n7OrTJVsiObT/SWWHDAeO+gUEF9Fo0Y8nQ2MMZqloSZFrtUs4RFS/f36yV/mzlMzbzSOZXoVEI+EvDfeZrm2TpQ4XqOCGmkoj1DCDQ0LtF21vuZKVaEWvOFUIjgQCyRGxanBbGGj2LAiJEtsc92LgMbJr90sy87RKrM2t2yVnwVv0zQGQGxSicJW2frrFmEcS0AultgSmQ7y6W4AZka6mkEAlmMHCYozGcVp+WhpSazMAbNTo6CAHEo7D3w2p6P5CSDJM14PgOrPhZKZuzCsUh6DgbMcpW0SmopwsPcsXlRRpgYuQ0WZ1/PlQLRG86rnpXUF8LgbsXkejzZvL5ceTM4BtPCqHviGW8dbHWzpkVUGDNDUrW0OKFaFlbp00z6uX0y9GTY4fio21+WKmHNnkNbyqcuDIBWroAGvXCvwqT42vKZr6gGcF8vIOAOZt61i/9K3EfP16pl0lX5U4+yGmaC9IQEVaFqmWQLGYhnrTXdqwKdJEu6XHh0XIFqwDKRIJBhCxpwjliWgeBtZhJsLkXl3mpfufe7RcUaitUKdJAFYEII0kQzAqtjFEchZAsQ/Y3FQxiIB0xKhjgKcS0BRxlUyq735daEKf80ijCUHLHNsraL6nRSgGRDUa6VWs49Q6u/Xu7HUqSM1KVd4dwzgxf40L1mgPVYd4FMt4Gog3opcNJRxee3e3W7yNUn3Dd5mlT7iorVYUKfxELDOhDcgJQAew3U13Kii+n68VfIVsO0kBNt8pPXQf8Dp8fk0s1ezme3eqVW7i2iIfwbui1V8lU6kG0nL6iFeFZoqYnu7nyk1u0AApoTV9rmaSxBIrcJXQuuqlWSAtQpyrFX4+tqb72BL7axiIrXKqtVyRUfX76E+pM5wC4Ez1hn6G7IG3+pgKyVAtTp31KxyDT51kayBU3I0u6xBTXi8ODBqtBNerrL18TvYiRQyI4JhxvxyMHOBqpW5YO0KBcX4UUE8MbpXhOUaWPbFbpgxIPjrSxBrZ29a0mrKbch7NYK5Gzk3O6jL3Li5VW1K3B+3Aa6uFmvt3EZoUAQW7LoF+2Q9js/HC2Rvt+7Cgl143Pt4yD2+GA+47s8uTqFIXLDr7HG3x127ASu6sN7AL047ZGH8mZvv4SqeARiy+dWywyEyrqJRfgJVZSp77VwYz+cDGIrLNEKUEUnwpD9hFxdcpXETYN30YfO9Zg2IJLhwWcZMiicXJ4gSbo875CVg7t2z8xxBi9OyOl19ixnvkcjv8prZaIMXAt1nzM8KlkuvWghOAVLIMdn1cmnVpczBaSr2Mm2OS0DwwKM5tAoUswUr9dYvXMSiUV1IkasRQXJRB6f8lTHafT6zj7fQRlXaFxB7oBOyMRLQjlc+sEq0zF6ldtn5+ORB12Jz5Q+HKHjSjzguHUR75MIoJdictzojSQWYWtVbcoBMwWbXw9qelmOyIDv4DJoVOjDGSw/ajfeOVXDIkxlOxsAw7Iqg1JmzwvZqIsiVK9p5B5MKAWOwjoVrLmixvbbNzmvCs2kf02Lz8HJRgIQmOCSDrHttNLN764wRuleMcAZOXxXkYQWf/aj1Vgfbuh4hAGHBFdhkda9VlORfDFW949pNrNWtov1Qfa4bY8HMmw26tp/r89lak7IoNNKaHHmmx149SQGIN9lV7WQRDNkWdQU51LnCo1kP2WyGvDJ3ZyOqbXCfB1fKSx9y0wcOLEhcVq9bWHXZuQVeZvv5JAGBTF0nsJjlVrGKtpS19VZPWi4BiwfDxOb2U8BrJest36lERFovzEjSKAbnkjwYCyIROjdAYIOA2Wbkx52VwcKtEp7FuLgKIHm2Wy3AShIoMXRGu9GqLZnANsg2D3q/3p1FugpI+D7RLOrgyk60NRKA0f0q7Uac677dW6rK1GDVoG6rN30sy0oVlLNF6gLrXrRF8k60/k6AcGYbV+0sGBDDZ4gWzLeKRi1oZUuO80aqtn42Igu2uQR0saCPRqmbU4BoQs4ujchYTQe2NCZSULQAuZ3v2u/gXYBKaxIrcmrSXnEztHm8/0GlVBIeO6fV/VOogVGrj+2j78pfT2unAZvvSgDULoK/1vdxnv2z1X26WRJuDA4MTPtmu8dbHWzZ28hSjJheTyQ7GClfFyAJpKvzg/Uk8QLwPSPvTBFECICoDfPbC8EQakkQg7TX0sGpOWcjNpO3a2iXUTrG+cBtqF89HNNdbeuwBdVkSUDpatsYjScWX0RrK1+ocYP9gtHo/pUzo3R24VZCeNXtVBfPHqeELhbXH2Yswng6mHRjVYVKLvz/1d0rm39KwPP5gOfjRfPFHeI6F58QMT90rQVEnSB4Jl0vt6KMYza7uqs4IXLBqXS4XwZ8MR1wLgl9yLiMI7qYccwdZgn47HyJfZzNIpBWV6H2txJOuXO0ZId9WvCkO+NuHvDqtLOsnRUhLS1BEKZ2Xsg5lOUg6D8P6L8Axg+CIZE94L5f79aKvXFHpXdhmFiQFVDido1v6XotEfcKlMdgRuh7q1a758FEKy6tG2RKcpsqqXdJ1grUVECO1oni/WZ/gr9vJvBkuA4AmD8owEIYPifMN8DyLLcARy8HdLeE0zcUqPPkYEWCKll+UAjn+6E9p7r67HYzAGCcEgILLuJk8qpxwad6iZxX0YYYTYM9+2dUIXRdxnBxts6XEh7uBzNN8Co+JGlCGnVeTLBgXzKbqbvPb2V2AwXvNlFQE+9Rai18OXjCvliXMQ3ZkvbEzUyigaAcfEonl9+9zNYBPAZDc7vnL9j2VlV+XEwBa3sZaD7Yea/IByuw8C4ApPISIKoohRGO1h6UXiCRVuRpzXxq7149G6pt+gzzMWxZGta/CajKUHaNaKPjWPvB5qQAVnk1oKGgtwN6Sfb+lAFWgheCj/v9TqLXqBDeZMLAoxlQDajtvRQNEEGLpbpSGEXczsvnmXVVwwCTT1wvqsXFIiJL48DWWe5p6nwm5I93NyQpLo7B0irYyKWJZlQhjcjFTQbMJOHFfHBRC6tKK+q5BupIYnKMJSFvJRuVce+c32ln3No+rYjmLVeQyDaHrITiPpm0ECQo8p7cJUrXG/P9encWbWZ7PpuTEmyzXhyoxFi1zHVD1QHsnnOqngVg0ziXaG3LKvAPbDbuQuazvUW9Os2k5MqpRXtedSyT5PtEFOO2DgzpDFXMzk8tvSLv/P10PcaSjU+qAgNgFYKAIby2VJcUTHLRhS0AQyh3nBFqpygZyKnep/U0VNBVYIWoj8fqZ/CWd5kDwLyiv6mKXaz7pbko0bqf1Qq8YlcK1mr1tcS4yW5WzE1rLZPNfmvlS5XitBGicAxPGKmJIL0O86mPU8fxlF5X9pHQo67qj1pvdbDFXUL5yIS2918QphtAdoAOziPrjWgtwb84/wIlAtURKIwG384HsYDoZOVKbOeJIYlNRYVd9DtaOyFMBm6q+sZlQ6SuQ/R6AeSDXTTxbBma+6o798zmt2Ei6ByMi8u6GkkD1j4aCdKb9VRr4fhFo4WAhZFOhFKAcsEGbiqh+d1mDRDNeFh6MCk+6I/oODfQ0e1id+tFnHC3DMjCuO7PmEvE5/cXECFTYsoEFavqpUTQtWKIC4qaLvGWzlPXLiybnzN+5/ZDnJeEZ/sjhpBxkSZkYTwfD7hIE550Z9wuA065Q/R2NJPRfB5ud5iGhNNFQscZHx0ecFw6TDk2H1vxrP1yP2FcCh6mAJwCwokgPXA+SONK8kTv0cjv2CJSk0H1pV4N0TEiTIR8Vazqqapx3pok34xJyZSMSMHOIy1fmoxWU3V74xpcKjiPhgxmm3O2NrMS9OyRZFMY8EQIEzA/K6vZOgPTBwLZme1dVWiSq4x5YDvm+rpCyFNYA3vl5lfZRw+2EylCKrjYT+hjxiyhyTUGtkr8sFsQg8nCLsVM1pmMZxvZfk5+LBwKJBH0ZAbrOFvXsXQCJPWZtoFO2W3yytHm0nzwmXitRJM0pHGdidPMjRpJXg0/chCKCkzm6KNDMSei7EmCt7JLX1vRQDgTulvCcomGDlchM06oCUDlByeB9DZmqMk7n98Fnq1TN6gvGJ9Fy0wUsG/ExCAURrEBbCZKCyGegTIQZGc+sZahYg20NTNjdasn445VPq+9uaOIF0Lee6CeuXFnaVspbToSpdcNBxeQoOAJjn5GA1yg6p4CrSUkvR+PX3RaKzLxIYdaUDfwjx3z3WyVYhcLzjk17WB4hpolNKecbWXYcUYkbijiUqxaFpczWyUv9ZHw/7aaFYT2bxPT6P3nhKfDCbln7KO3sLJVsDXbrSpQnz8c8HR/xj6Z9V4fMvr9gpQyxpJWyz8x9aq0cSEC0FRtalfC0Op27PFkijHpSJDT+2D7Li1ZAlgNf0B5I4EaTE99temE3fNMK2qYrEqiicHZGRBRH5mor6WPBwgH6TR3sSakD+94reDHWprKTg2DEbVhMihIu7+lsJuUYO3MBF2DhQB0ik1swuQIuQk2aG9Vn4zRAF3eTq7J6uwAkBgLUiwILC4i5PtCMD/rIty8b5lsrstBUTpZNQIIdgwwrXfiqrhF0IxVD5r1UVcAzgJpBYYbASisPQ0AcrZ5dTgyyiDQnRjoaSbkKoJRu4LbPdWTEEnW6TLnI09GKre3fqe1s+hIdCVHRLs4zpustzrYwlG73bBg/pIpjJD38aGwyrAijQmQgcAzIR4JpTPTgkIMiq5H3FrIurZLXZKx5NCCZpVmDKNVpLJzgMXimc5s7SBlbzdsutjSr20KZb9wltDQjwrgdR9IYrWManBUnIMeDML8OKuSy2xoPlKUQngYexz6Gbu04LQkiHYYYsaOTXRCQLhdds0tp3rJDsGqUCbFjIBSaDVkaC0bbe24uQSnDK0AqBpoExfkHHC7DC0Qfm3/CpELjrnHuSTcTrs2nwUAhuL5wwH3zw+IH1nm3LFl3teHM4gUp6VDCualuwhjWiJ2aTFBDd8wAD+NZBuO7Ky1RYUQ7wnpCPQvFTi+7yO/U2tmkJgwQZgIpVdor+uIJmz2AIJJBgZdryWyiiiOhPFL2Sz0nApk4B5qnNl685v6nP9xhzCjtZAJ2dRZYQ3IuwIdYGbzVOlBgEQLksV1mnXD8a1AJC0EbMdrF9LGTFSV03a2r9B9hEZqftcAHIjo93QwZbhAimkxX2xiRUoFh27Gce5wmnrEIIYTqWI3PZraHvy8yRwM0TsUxC4jz6FVuMSGwxE4/qYWEkFN0rEutvluTNkSjpkRHhjDF4T5hjH3Ap4JPKHtvU3HujiIjV0PnaxbuEDWTsSy6XTVZEurpaEpbtXuBud3RNSCHgKWxYW0o3tHZgWfGbwQ0j2BsmvfJtiX3SvmG7OcqiizdlP5DWE3iqwZp3Pdqsxa/QbL4EjWDaJNg/vT1mNU9ddFy6JrlVrbIhpgGqcKq4jdYaTSA6CAjgHpVUDp2VCIHsRR546edYXBSPgEe79ptOovsGBcIlQJ1/2IISx4tewwS8DLad8q3n2acZEmC7pQPCw9jrmDit0A3BejPcxsxkGsGM8dRAjLE6tk7/IAUUbPCyZEn8cAT7ozJgkQZdzl3v5eBswl4JztOFMozVTgo8sHxFBwsxuxiwuGuCC7GQKwtqk7LlhKwDgnHGNBiYw+ZXBh3D7sIC44T1GhKAi3EenO6F9l8Aw2vK9s36XVfy8CN6a6VivTJkavDI3FgkS0+77KuSpg93ExYFTZAxjKqtkLa1WqbjNsq5qaZyzwyIhcvXKm4mbmZJWTiVb4Y3wc1WaTdYthBTkzqFa3Zv1m1VlxgxaKJkmrqYIzPdCyd9peo9wyKVgrVW+910wfndD3JsVaRzeHYW7PneeIMkYPoGtl2PjIm0SGo0JDMdEQNe3yx/xbtOe3//fKt1b29XNLXLEzsheTqVSfGQdHEp+9Pd2XhqvRoBDXtwZgGvp1rg646QStHUmv1M01SMxp6A3WWx1sw8QoRVe5sdohmG3gPTxXcAaOvQ+/ycBFea+unewnd1scVhu2CMsEZ9+IlVpFC8ACdwen4aAFSnX3D/v3hlJCBCraCN1aUXC1XR0IXND4Yspk2TKZOwktjkpUQCM1kID22dsxhqILLggO2MVYiukZ1/ktAehCQRcKxhIxloSH2VC+RYzqY4bwSzMyOC+pfY4QZSWv+9y4zIxJVyBTbRczCbJTfvqQsQszmKI5AS29/T0b2GkRblm0KGOSiCf9qfFvAQNNgdc2V90AmJzmk626ZTJTewBYxti8SE0s3r6DeAamp5YwLaf1fL5f78bqbm2UVHpLuCr45hHghaoBCdZ7FWiJrvY2g2RXeKqryivWwGzzXrV2cG1fbiglVVBB1dqSFOz+b0Gp3uuCNQA8ei9gdTiHFwn+HFfJoyAmwC/6yBAAgLevVw587T6tIjQW7IuugMsuZjChJb9DzChKWEqwwDkzkMqKS1WfiwOrU5pSE6aQ0TAg+ggxCqwCH5vPXitSpfWcEMwpySti7awLiMzQmZpSFJ9ci76jdY7tXchmYeoJFqpC1LYVDqzjRIJ1Q+QdCLb5OiOWiAJDo/FtRP/C6DxlUEw31i5ZLsUkFIOCFkZ3S8gHRtnCu9XbAt4CLgdtmp2Qjfcj0G6W5apYNjpxC5LWClaHj6+taQvY1spGNlm4mlXzZEpH+aDQThGOlmqWoUByQPo02Tz2wtoXPBpdQaM2P9uq6lR8dhJTQUwFXZ9xuu9x+vyAw0dH3OzPBorCavh+1U0AVprNOSecsyG4lhJQ/KYQWPCurR1aCDRFyPWCmMzh5y4P+P3jDQDgyXDCXAJOuWugp2occDubEMZlNz3i3tZAercMYA/xx9xh8eqXSHHdj67jaujpsSTs0gK60oa8PgvjPCfw886y24OsM7m94PyRoTzBaoCT/eZaeL9+4lfeA/NHxWavjprlhVc5RpdCBNYxTpvz+fgHPq6SyVAKtaskhSHniPgi2p5cgOVGAJeXVQH0GFtAREAbY2lAE2dALwhRDOS0AVM18wGFCz9sqErieun+emFXTAZxCWtC6QGEbjtQ8XsjrZziLIz7ecDtNODF7QHLKeHq2dG8wz87WOX4wQlEimUJSKlg3y8oYvde7ApKMKctAMinzl2KuM2PtTAEsmoOZPP4RvbAlwQo3LqUlK1jqJ3aeBC+HbMC+4KcCEBA2TnFKomZJrxMCBNheVLW4kphyUD9//o6sPPbOL41kCtWMZFS3YZ4RUm/EzNbH5CrE8yDSx9iZ0PvsrOTVNtEDeVXKTvt/LrKyHa/9ayzIQ9/kKRftKyyzkBIavaJx6RvoN0oygKCXUAaYBVvHcYHc56gYgCr4sdkotwGOW9fPOz4yFvGFGyOW2YGR4FGk2UzLusOfLIMtHferIAcECXtZwAw5Yjsgv9bwFQzN9pmeWrn0STgBFkZ59K1QL1z0NNUIobqPevVdK2Wh7A0UQ3A2lVjiU3tCgDOiwG7RAkpFFwmSw5aQiAm2DHEjDFHozwJI2du4AWpIBh422i3fjUyKOS9jNQ7tSTBjD4EhvUoDMo+ztnwKh+1a0lXx6/tvV2ryPo7r445W+Ak71g16UcfJzW5v/omZG1Qql0ywCVpw1qFYX0dYH2vBpCqFKWqxMSCovzaY/wj+T5YCC2xMOxGwOySqXkx3+eGf1jstUph58maxd4cxOVcXc+ZCkIwtalqcN+Ur/xcVYEerdW/1I9ns9HaLaRse6BGoAS1PUeBUufU3tlr+3wDsinYZ/I52/Mb4Gl7u2/b1a8v3fypz9tQOskdxN5kvdXBlk4RdGND9/AyQZLi9DVpUnxzCCBRE6HwuaayYrm06sY0Oz1bHX0Oc7nJgNhAVFCrRlu7OcPuKj/p2iu02AUBoCGLV1HrTWsqKjQK8t5uNEmWWRf11nZQz4ZdgpLVABg1GSDYPNlfv0L/uyFjniK6b/UoPTB/eQJ2Cy6Ggt31iHkXcTFMiCS4nXft5klc8LQ/YSwRp9yZsH9VZ1LCIc1IynhezEWIjnHdbIKi9MBwmHGxm/Cw9JhLQB//T/b+LuSyLbsLxn9jzLnW3vv5qKpT53TndPsmr4m+/7xemGAUghd/SBPRbiE3yU0kQsSQiBCE5EKIV35cJBD1QhG9UcyFGvEmgqIiSIhgG4wQBBEh+cdXYzrpjzpV9Xzsvdaac47/xfiYc9c53V1H02+6TtWEh6pnP3uvvdZca84xxm/8xm8UJGq4yKspVGlpz2Va8d9v38IXbi9Ritb2/Z/X7+EyL2jCuCszniwX2KeCR/MR//3mLTy9P8Qm9ujiGPe+geJcN4ti15IDlrq/3ynD8m1zJEjUe3byQ4PmvpOA75OS6N6M12asH6vgBICVn+HtOTdzVD1tJJbjo30Npz6gYR/OdHVGsQCYGta3AVoZ6WhMVyE0F8K/qNYfe0iWZhXQESN2KomHe/cgL9kxQyJOkHTDLbY3JOg5k5IX28agEwcUriRja2wAWGs/dbCXIni2Ko8ip4bL6xO2fcJ+KphSxcUnbxXdsjHNBaUkPH9yqRFeJdBVQY6ett0wRVtCIXCuyHNVkZxFy6RkknAK6F7zrPVBRVsZbUehjhcpUo/wjdDWvK3qooEC5Qbs9X5MzxgtAeVjmxrxxYUOoE5AY0gqmttdUydnAR1mBvTcVg5GOJ0oql2+2nilja22xNKHLS1AGeAYpZpbUnwUhxi90g8KZjwiHW9otQ967sa9HIOe43wGolX8+2LEHO/FED3bAnXPNwy1GtuzpvdRmjQclFQpphbuKZ3hvHKuKipOyj52acVkzGNAa183E5iIqbCyGQjUQ7V2WZKlF5gDpt7UtNaVMxK1YDV7o+WJel9bAoKxqE3ftRl8sXPwwvkzoGHIJzUQ1ppwt8527hSN7WU4fzISiBjbM74c6K0Sx/v0Zrw244wAwybZGJKJQ9ccSw05RHsG53pZj0O41nYuJBjNmZcJCHKTf34UpgEMDYPliF8w5uQhs/9uHxk0gd2JbAmal7WmBWfi/pHftPWbraa0pjhmbRSoFqB7wDRV+xtjzgWVGSdrX+nz5XPi+2G0/hzyrGxGylsInslZBmnKNkbLe6vIhCFSwx4ecyaIft/ePYiqy1Nq9C0Zna1tRClhifvW4XU6u5b4LhqeFX/NAp/Xh418WdC2CXxM2L2nMEF74N7RQEICujEjh0MIaKl7W26Ejf7NN9qaDVcbhI3NetLarXqpkTJZBwiy4NcZz2GIHD6xG6P5X7KHUo2qlgdRXwiieVxKZiAaGxytZC1M6FqfAnBuSsHfrdhPBU9+t3pZKZlIuLEHiRDN1JsQEgneOWiT9/sy467MuFl22Gf1YD1/I056OGbQiZFOhLoH5LKC7hLSPaM81Av+jScPIQL8f979gka1Qshc8WBatcxIGB873OJgrOIqjP/29DESCz5x/RylMU7WKq80xtW04uLhhsVeu5jWIG09uT/gyW8+BB8KLq9OSNSVpACALhbUyjjdz5A1Y3qStfnEgwLcJfCipDPttIKuKPNmvBaDT6y5N3Ou5bJiPTQt+9gIqArdssGXbf+C8QU0z5ka6F5lG8skkCLBlkVuKqJ/sN8tYgWAED4H+oZPiPp62lyEH8OGD0Qj+2rO78bgE2F6zkgLUA8JdRZsb+mx3GjK3MBHbR+4XTGEtRRIWEAXBTyQlrSPraZifFXcm3FNSbWPy6qiHNIIPDXsrpdgB7OTE7ekVQwC8MI4/BZjfSDYPlE0kj4mncOLGjA97XQz9ZaGqNribrphbFcNba9oIKDzSasFAJNArgqwJHU8XPbRNBSCbQ6FzGWnjR545bO/nTkAXoHi0Xax75m1jheFMD0j4PblHPVX2tgCUM9nEpQLoCWEodUH8wXPxaO4WXoHmJ2EOIZ7RqEYY+U6/j1n3Hjq7zsj0BF6KRAQiXUxKbD4jAtnEyAQJQoIFNIxabHeMLnXfXmdXOh3Cg2C4qoEIybN2KzY3DVQj+uE05axnwo4l6il+9LxIoxyFUIacrVrS9pxx0Xas8FQAk0lTXoOUdQ+zEWDGvWZC+7KDjdlhyaEfdpQSPNCu6nEe5r0Zu9+zhM1tNSZx7Up3CVCoLkiZa0BdGLU6Pyz3zMW9fi532fPjXmq9k1g+3oNqhjEE6TXttszRJ4iMtT4LNIBuvGTc0U4iEHDSbR8B+jpJzfUVosrkHN0pSEqHsgM2dnm76dgQYOYE+9r0uUju4FGF8/PanBapp6TtmOHXrMduzaKvWCUVRQha0jCvQTJzt0ZumwayESCsmVLhek+UWebiyUFOxuriXJ4Co0jcasXYHPWDLZ1sQmdakcWBtTA7AGKcWE8LnGDKtAAplBHKvmFeyTjfRsmfwzchscAL9f059U2trKp3ma73nD0XoOnFEISbkTZumZEPd1VAX9p0iLoB0A9KElGWDQvIgoPNIbWiA43JCBeFvCmN75eWk3uZlCHw7xkxrEA9cIo+HcWXe4HnMgN7qBIo6VHsD65HULJd4T5hlD20GLsBwRopY3qBO80h7Iu2oe2NQoFmJunF5CNQR/T+tW1ZTw9HfAbn3sLeVfx4PpejRmAw7SphvHpAktJSPuClhjFzheNILuKutdTvT/tcNhtEV2uNWNOynp+mI/4jeND/Op7b+MT1zd4vLvD2jJmKXgwn8DQtn9Mgue0B6AayDsumLmaVrNCzKUx7rcJiQVvv32LORfsc8HT4x5bSdYCUMXRAQUyaGpdAtMgpCjPCvWgN5Ht6zS4EKpvtlYapspAtnHfJn025gFeJoSwvWvvigDYq6KRk2fSkQA2BGgSFd9ZtVmKzJ1vEY+cG1dAo1UnMxVCc+9Vhsh32PTFcszFCJfbQ837uupUNAoRbUZQHK5lGLSqJYachpSSczaM8CRCln8VLKdJxW3M4Lk/USuDuYFTbzjQ7rQWhw4FkgTLO7qf5ecJ5a2C3fWC8v9cYfce4fRxFe1p7KkrMolLjSa3hxKkMi62H5qYEJDU4FrzeDqs2t5vNeRRgHbReTsoDFrU25aspFRMzRQAKXqZuxMiWaUlRSzvLZrOo9Tvw8uMV9rYknWKiF6SACCCNjIFG0CW0KcKNZgmPlEOQJs7zBASidINs37Qv6MhKMpVP0eiOYVolTzmU1/MCRsLUQhDc+QBEl4J6WQfzf04zaJHaoBMQNkjyAKyJKx5wn1Wo5RZ6+l4YE96Nw6HzLyvbLEIeNoX5KnG+wTKStYynH7usdkUBt8nlY6c1BudzMguW8b/ePoIc654++IOTILbskOmhkcHvbjbzWQbhUOH1V+/Oe2wmwou5xVbS6iNI7c8Nogng439WqbUsFmHEx8qMWkbg6MKHrG492u58DfayK/X4BOpVLqnkCpBNtsOHbXhQVEqyv7QkTN3rO11l0LslQ9udeyzYeg6ZOuM5Haw8IjUqKSFVO3MyZmC2A/EjfwwZBJUj74inyxndiAaqVhZk4DjuDQ4m2w6xwWAmISqG10iASdox7EG69vLWrKTtckHc4dfqRJk16NIL3cEK1O5XlecMuv1T8rvEGOIqzOhndh4tVK9SVA9yjW1LS/h05M3IZDc9Po86vS/mwa2zBYgeY7WUQ6PnsUMLA33bxo2dCv92a7kZTvsvdrGNmWHHBQKERcgPFRwbqjHrH0ercyHPDJt5i1dq6i/TALsVDFGSlLW4L716NSgSLLaVhj9XXbm0VokrQ+TwSNjvhaA09x5JWux14Z6Ln1vOgHzDWHJUKdhooBvtf2f9rGUK3UcqGoeuUrGiWdMc8H1YdH6t9TFuX2xcBIImc4pSZCRHl4fo0ZOiUisBL0RQrKpToeKesOYnlutMjekJNhPBacto5SE43sH0NSQv0Gf9Ou84JA2/K7Lp3iyXOLZesDO5CCfHC+C/HS77nB7t0e7WHC9W7CUjK0xHsyLipsbtLWWhJQarkwAHVCy1870WwHg9rQLOTtNKeg9SXesKMbOSqwcon/JWrk346Mx8j2w5da1hBeLdtz4epN3hx4H8f5IDWW3uDr4ZI66czeMMCQmfOMM/tBeFzciAj6UYDvTppKy5YogOygsLehCPEG06t/ddg000TnZ0g0vEERRmmvUEDd73TsHefetOdfoEtbs31I0yPDIlUhQCmv9ru11rbAGQBOF00DWcCD2yCxo1nO3Ncbu8VF76W5WasgNVRJosZrcXQOdMtJR50l2bRAHsXs1kGL93GhumgLw/dfWPy0G8V9UdWKsDaL2t/U5s0YHmx20ETA18L7CiXIu0FEeNrT5NWgeL+Y9RWG3E6PMI6EkEDTUvXsz5jU+yf3hd0iHB9jXal6pMPjG6rMcbsjDQ2RQZLpXyn/b94VEG4OP1h7LKe2gnns4JV0HSZCeJ0w3akiXxxKSY9Ts/9b5oqEZsQcKYVs+BElQlozWGNeHBYmVnQxo3tLLg7zIvDbCNtSxHibt2FNNsnEUFZ9zBQrQbieds6sNINHI26Dzapqvu1yxyxX8tipBvX24B5Pgt07X2KfNamoLWtKG9UwNj/ZHVGE8PR1QhfDg+h5TamFoa2PcbTNybWeqUQSEtONSMo7rhGXLuNhtyEbwYhaFvzc+FxFwRMHX2UVD4xdhiDfjozyWx0M4QqKMf26gkxNu0Nm6o7pYQLgEC43id+/+JZNt/qxEmnSTOjekGHzJyp6vB3X2sxs/WJR6QETVIRXryNvzBLboOvrkHpMSKK1hggcBzZ0EDxxY1wVxQ10n3Vd2VdNh3mCACtj1kFlQaq+zlWEaWjNjReiylgujkctMKoRLXhpDQNeLlj6Vg1MP6Dm22a550wqLukdHp0SGxvPozG5WKLlsA1PanJP0ZAJVmEyuve7MbXO6Qqgia3TNR1Ob2rVAMMQZy3MLiV1pr4WxhRrXKOw22MIS5pQaQJp3UeiwgUrC9JxQD0qqOhMLh0GKvu8WUiOYBW0m1EtAUo0+k84KTmZUnaUMkqFHokXD5hEHqcmYkNKA6Yax/zxw943A9qAiHbsiDAQhfO1QDAmsmBoBZcnCqLYS3NAwCXJS3eBaOSj8rTFKBRJp79qdkaW2mnC07jmZGxoEh6RebrpTHVlcAb1Wz3KeJvV4mDdM3PBgf7L63TvclxlfPF4BO+DSGtJnbprPJUHmE051wtPjAYkVat6qkrI8sl7td5dg9IWZqWEVbSG4lox1mbCftyhZYm6YJmC10h8K8oNPlM3d3CAvy3J4Mz4SozysYKSAXCk30CSQ46zRJiHkDM+wWFuzLAM/wy2bv98cYJoasGmz8c3LEiup9rI5+jKLRk2pQUQZ0JIEdSaDmz2CNgi6EPKd7vxCQNsBPFXIXTKhHFFZRntDdLkh3Q/JIGD2SG9VspOwGs/GFKmZxE0RsMSRxik1RWpppYxQk5saxFT2tJuRMw/RuSxp2GvJoGhbj36+sD/DmrJ7brV5tzSPkEcoPw8oYUmgk9XBsgRJdn6q+/ryjn5X1C4P0pWy2ZzZeaZ71mDpoquJxWMwaeMEaQDqy+0dL1eNO4xf+IVfwPd8z/fgk5/8JIgIP/dzP3f29z/1p/4UiOjs59Of/vTZe548eYIf+IEfwIMHD/Do0SP80A/9EG5vbz/sqWgHCWv27Ml0KkqSkvuMtqVes2bkBUmC9a2GulOSRNTJOuHBGLdksOJ23bA9bCgPVWolP5mw+yJj/0Wl2+cjYbtuqBdWt2XwTts1lCu9QWSJ+yBHkJEjzDlY3q549n9XlAtRIfKseY12aErQWDkIFkBn5lED8g2Dn2fwZcF8seH2tMPT5xe4/a0r3N3vMBtk7EMEePqlK3zx8w/w3t0Bz0+aP11Kxu0yowmwy90oa55U4S7eTMosqxymN7Uup4zntyqUkbiXG/miJZKQXrzddnhyvMCpTpEzZqiy1WHacD0tqEJ4dneACOFyXiFCKLVH4usyYVlz1AzfL7OSwSrh/qR532ysyOXzF2jPJ+DRhnZVdSFVgE5WGpAFtK9I+1429Gb89o+vp30DQDeglSD3WfcRUuNXLzSfF/WbYhUADYoyzdpPFmLGwEt63K65uENu1tbR0K0k4BMj3TD4JoNuTRmqErYlo97nTqC8aJFLJtcxNv3g7VHF9qhqz13rfCZJG9dHgCjUe7IWE3iARrpOfIKlvNoxo5wmRYKMH1Ea426dsRrzP5Fgst62bAH0PBVMjxaky6KWa2rAoWI6bJgPG+SyoF5XtIsKuSqgRyv4egPvC1JWg18rY1uynlch1KLrOCBir+kfomI6JtBd0n3fRUaAyOPKpNcFy8tCCOvjpmiGG/+TKmOhkjKiT4Oc5a4Ch4p62dAOTe/jxpAnM2RJoNTQ1oR6l1WqcxtEB77C+NDG9u7uDt/+7d+Ov/W3/taXfc+nP/1pfO5zn4uff/SP/tHZ33/gB34A//k//2f863/9r/HP/tk/wy/8wi/gR37kRz7sqQSzLHKjDaCCiDyjDKgpNEyisGvbex7UjmN5U7HCaBnEv9tO9ThpXxWpWIBkP7xaje3c2a0xHArxiPQF+UZxKBOA7Bvo8apwUeufD4WU6qpHBuUMZSy0GbEqV+Rcsa4JZU2qn1y6gRrp+zgx6JiwbSlkEL3xO4DIewL2rBocFAGh56WDdGAdPew7mlDoLHskC6j85GalRGtNKIOIhpO7Zsvl1mLykqmckTe0GN68cDvv2lSzuW0JtTBK6Q8/H0n1sPcbaK5WtkRRUiCW/+E3MPLXdHxd7RtAX6tWPxm/p2Etv0iKgj37aVjL1faWAWomKytxrkfzshNWRIoLwnn1Y4sFDGxolTgfxY2ioWVUSctkdmr0x2hazCiN10jjeRskrj+WuzQBH4+Avf8zoGV2o8iNG2J/z5wr9odV01Mk4NyQ5qa67LmBd+YMTNr4ft4pEZOHEh9PAfYf6n1+HXkaKwVE55d9LmzfV01oi5ztHo3RaD2o4QwClCNdrm8wlIdS0muRqfVovOk9i/KtqvtKGPyXGB8aRv7MZz6Dz3zmM1/xPbvdDu++++4H/u2//Jf/gn/5L/8l/sN/+A/4Q3/oDwEA/ubf/Jv443/8j+Ov/tW/ik9+8pPv+8yyLFiWJX5//vy5/keA3ecT2gSUC0G+07Z65VJQd6R2i4Dp1mjxezVm6cTdcPmNuc1qoA3iaN4/0ZGkQpC5YXvAqAfpTQfcmCYotg+YfJoSHaLpscPcReFncfahwTAAYqHnO/XWNvNao6521wDrl1v3sI4lGjEfskIy262qKuHxinm/4bRlLFvGtubuC1hN2+VhRU4NN8sO1Z2LxliFkFhA1LAW7V+5vq0LSmtagbarSj7bAJob8q5D0W7gb4x1fD0pC/npehHR79OTihNfzip+cb9N2AuhzYSLacPD6yOudwsOeQP2Wu/rghdvP749i6CJBPX5jOlJwvYuwEnPuzVCfVxAqSGlBp4a6r52luShgqeq3und7ss/0G/G//b4ndg3gC+/d5BoRANGdMaBQOHQRKCbrI70Y4tsdg3IDWlqKPcZ/DybcVO2LIlWEFAF5meMuidstq7rlRGbNoryUUmmq14JKADdZw0EdioRyzt9LscGA/mo8HO9wJkz0CRpDjE34C5HGpmSQC6LlgDlakiVHqsJ1BjuKkCIqDaZgXKkKeaxZHWSjc/xYL+gNu0oNk3KkZgmzfN6vTsl0WqNlSHESEmrOVoFWk0oq65dSg1ynHRNzmb0TKoWBsWjKA8G0OCmcTeC+cmkSOADcyq8BSnQnQ8LourcVHHwLtlzAJTrCjrU7nAYfB8SnVYXXN/elAh2l8FHFTKZnhHk7uXM6IeObF9m/PzP/zw+/vGP41u/9VvxZ//sn8WXvvSl+NtnP/tZPHr0KBYMAPyRP/JHwMz4xV/8xQ883k/+5E/i4cOH8fON3/iN+geh6JgDwNnucN5CRLhDVKafQxQ8Q8wD9dci2h1+ACM2aN637RVqaiY9FrJfXq9pbMVoZjN6Zn5sLwOwsoK2ev6on8u5x2XHGXIgzeES7t4oLHpPZnzvTzuUog+/epG9ptCjuWXLWLYJ26YNALQECCYUYeQF81JdMONsbliQUm/N5bCxR65Moq32ivbTPSvjqSmYjwBM3UrzyJORqHa54JC3kGvc54JpiETZb/xQduWlCjxVsJVwEdAL2BnRaDtKgt6M39Hx271vAF9+7xDqCnCqL8yalhKoAfX9gSxCstpUj8hiSRMiJTSOWL9AR4DEHG0ToOhrXWtHPV+r34Mz1vLZ8T1dFWkrO08r6wnUzKO0JL0FoB1LvMfzYAFeRMF42DTPW1oCu1SwywU5NUxJI9kpVS3Hszlinzvbb5xHQcPaJR7OoSGUmeLvrvrUKPb3YHUDvXTHnA/VUR+uddx6yfbLkIbEOZIYELym28iY6r43sBPfhtRk2hTlfJnx206Q+vSnP43v/d7vxTd/8zfjV3/1V/EX/sJfwGc+8xl89rOfRUoJv/mbv4mPf/zj5yeRMx4/fozf/M3f/MBj/sRP/AR+/Md/PH5//vy5Lhq7WMkEcNMiclYjJAzke02KlwvLwxpsIKwTlG8J5YIBVM3VZDFyEpSh1hQqcNUmzaE2lTojKE2/EPKtJtLbdYOUBL5nzQc3QE6sfW/3asmbkZyU7MDKeD4qyapeCNqkTF9l8VEnURhEko6M/RPC8pag7OQMYsm5Yv/oFLW167MdpicZ28c2XDw64nQ/K7Rs1HsnTp3uZ7QlgU4J66MVD66PERk6mzmZRFy5zx2aN8IRJ8E8qbjELqncoxpYRmsJW0s4bhOWknGYNlxNK9akuSCHri+mDYm1/y2T4HJara+u4CJpY+omhKWqh01AELvaRHjwDbeoH2O4GNhYkI8mWJfJBEpEUQiDwlRFyL20N+N3anwt9g3gK+wdhwpshHSvaJhkoCXB9qhBDrofCHSDJWj0Gy33sjrboYnsTp7xPda3WjcIDbE5U7OG8zRA1wwITDI0STR0lwbNs2YoZ6MRygNlDdOR9d8CtINAhq5Zsms9gIBHaWpsNUrjcJSjLGZVEihd6Vq/36aAi12ZLdtaPMwbEgke7bQpyC4V3G0zbpedOsip4n6ZUUrCNBdMANKVzmHiBmHCnDtp00c7MIQZ8xcVMdgel4Cf6ymBF+qM7tnm6JggLCgfX3UvPTFkMkTTmcVtMLhM4KkAEzTCXVm5G9amtJqhb5I0YNlV9WMWZY43d8wt/SQClD1BfqcUpL7/+78//v/7f//vx7d927fh9/ye34Of//mfx3d/93f/Lx1zt9tht/tgmG+7RDSGV+q9TggXdA/SNtwYpH9rhrgGfDAm2m0BiX1OPJILIoRByWMtrQ/P+zpjUQ+uDDh/vjyHSgJh6o2PzRB3ObRuaB1+aplMyQrhjbXGCgUl7W1bNmU7t6k3iR6vn9A9WHI2YSUwIRoVeM2aCA3F6/oQR75kMFSeyxm94GrsZrG/u/ecuYUGsg8v4xmPU6wWOFtzgyoNp5KVfAWHvhp2U0FthLvjTtt+WWF9aDz79Q7ebrAmNw6I6s34nRlfi30D+PJ7hyIaFmUmFWMImUN0ToRUZfbKyrF2vc1kyH8C579PHqF2qPNMAtCVjGw9E9EQ6RJE5PzZHSVo0c+x7w/QaBXQIGEY0gwFM1Srizeosw/gTO/Z1yiRit9UvNiwRMlS2SBAX5dE6pyMKFVK3cgSqfBMtcqF1gi1cK/bzdowpKU+R+4w+DUrKjAgDX7OSXTO/P0voAwATKFL91ViAU/Nms9r4NRGMtyipaPi9bOGKPYuQGInBE3jVXnf933Q+JqX/nzLt3wL3nnnHfzKr/wKvvu7vxvvvvsuPv/5z5+9p5SCJ0+efNl8zZcdDKy/+6RGYGVlyR4E+UlGvif1MLNgesYQJmz73qy47gXloinTbeUzFSFJAnaZM/M0iTUvyPeseVgmJd9UfZiFbPNmFcpQQyxBQXdq+vvgiyxolxXtEkHkEjNyZHBGRMKs5UULqYPhFHUQQppxt9vQmnqN+aKAr1ckQElDBLCxAIkbatU8yoMr9VJFCMdlwuk4Y95tmLLCQsuWgedTyKRxQXiaba/1ck6E8kYBgHq9RbS5wMQN87xGxJtJ37sNxrk1xnHTRvCX06otv6CyjyBd2IUUHveIno0lqRAzY7mbQfcZcqigrB4rgK6dGvA8zBki5GcJuH1jbL+extd034Dm9SVV1MxqcCeJXqgQioYk7ZhVDOVWay7bhckpVosi59Z9bWvbJocaBsENZjtl0yhuVg9qn9o1aypgpL5qnj5pKZISo7T2V08ctv/AUDo75yUp+eqREpa2U46SyJoEIhmypig5BPsa0Ci77TVfO6caxnPsM30sU5ARdc3p3+ZUcCyTImmlm5OUGi531jhkVXnVR/sjTmXCs+Me65pRbybwpZKmprmgJeXEqEiR9KCDRfc7K5MKBa65dZg/NVWq8jkkdC6MkObLq+Vf54b5YkVLDW3HqMekeVdzjKYnuhesBxM6crhsU1IZpgYcdb7Lw4Z6eLnQ9mu+w/z6r/86vvSlL+ETn/gEAOAP/+E/jKdPn+I//sf/GO/5N//m36C1hu/8zu/8cAf3nBtLl9szSTItXpaz6A8AUDuL2H9XWr9FeUZAcpUQLSFS3U9XcyInOiWFrIPdvFrk53DToKssxRiH7pF5VNz6IgJw5r1G26/RUBD6tbkRJigV3RYssxIinKEsjVC2FDnK1gh1Szjd7nA8zsipGSHKcjsvRINMWtjd9gajj5qgNo/MTdvpDXCsL8p91vzOzBWT/fgmdNwmHLccMpH+uX3aMKX3N5XfWsI+F8wmXLHVhJvTDqctq1dtxDSsrDR9v/3uuFgZB58YfFTZSQD9mt6Mr4vxNd03gI4ceb7PN2dnG2clRAVhct9COnBsgg6gl+bEC77JG5rijrYdK9j8Y6cpc6bHz7eq0agYcVKyagE7D0V2dsxRT9kPYWudztSWDOpOmn7SMkfbq5ynARWLOeQNl9OivamdhWx/m7hhqRnL0ANbkSgVzHEUC0CQJreSUIWxVG1Kr6VCakx93yKfA0cXnMvS6BxF8MqRMfIX6ixxF7kYX/N72whSSDsUWWUDGP1eENB2+gOb/7PKCzPuMjeNakdm+lcZHzqyvb29xa/8yq/E77/2a7+GX/7lX8bjx4/x+PFj/KW/9Jfwfd/3fXj33Xfxq7/6q/jzf/7P4/f+3t+LP/bH/hgA4Pf9vt+HT3/60/jhH/5h/J2/83ewbRt+9Ed/FN///d//ZRmFX27QrCzTZrlTvyFtL+GtAgYnA/qgV0K+N5HwBC0VqhRQdFoUg6+VtCD9aUJ5CPDlGlArLSoBKbthsl0KcCeQQwNWy8uQQbT3KgMph6q7/qZSgWhQJZLUzjpRyOhRCbphJoHsW98oHO46JdRCwKVJF+46FHQ6zmj3GflqQ8oVy90MrIz0PKNeV0yPnxuzUCFcFx13ohSRYLpaoxF1EyAdU+SNtJ+tnMHEbJ4xU8M+9RpW72nrhKnbo0J8e9NWbkKYuOLhdDqDmRsIN6t2DfqGi9t47ckx4+b2gGkumKcCFHWWqLDe00tf+BRQHi9k+Xz9vRykt+16M74m4+tp3wAUhaIEK9ux/WFw3tmZxL7mdho95mdJOSG2X7iEIUhQfYP37zDIEkAYWje83krOIeno4jXAo1JJxe9zd7qpEtItox4a8KAYU1cdAO0UpJ/lJCoVIWR9bdXwyNw6uuNavwsDApSagEl5F1fTgofTEc+2A05lwmJpnylVZNI+1EUSbtcdiumXl5qx1XTWnrMJaRRrqnDLlrGcJhABeV9QloS6MvKkzebDIFpUHupTA/lRCgHUa4fFAhyeak+rrQkoMGlHQw+aBlMC1t7fNv8uaNJOimKUB+bkW3BEh2roKcF7DuNQIz+O8nJ7x4c2tr/0S7+ET33qU/G7kw9+8Ad/EH/7b/9t/Kf/9J/wMz/zM3j69Ck++clP4o/+0T+Kv/JX/spZ3uQf/IN/gB/90R/Fd3/3d4OZ8X3f9334G3/jb3zYUwFuMtoDVnkv76LjxelDc+Zy6JMhWVAuzCAYNOP5EiEtpwEAusngVTfltmPUkiCnpEpK5O+349qCabN6nh8kHE4emdrfohdusVQB2+8mrOGOQQyrDZNJINSshZSWIyGJkgaSQsPeCivnaixAPV+2Ehi9eKA+LKB9DZlGb6nlwyNHeWEDQepzCBKwMRKrMNYXEJVTnXC77vBgd8Kj+Yj7MuFUJ2vvx3E+BM3jTtyCGKWKUWvkh/a5oDbGqWZUUchZhLA/rJHjTQ82VKfxW4TfKmsZRWHtY5qAcilRJC8MDGDgm/E1GF9X+wYAfjIBj9TINO8RDYShdRW6YMZ6vjZ7nlfhXaxAJa3LDB1lNxau6DS3cJSxMgRsjUgkNN2xoqNa/vnh96iZbQhRG3FDlEyBqQGyJmyVe1ceR6rMMXDHnSpBkkG0VgroFQIAgi+x1oRjmXC3ztgq43IGkIC1qWE9lYy1aLTqHA/fgz7//KD8mamhVcYXnl+huQMi1P8/5mezWClUh5rEI14xVMHSZ3GN5hi1LZlKVr8PMClZTK1rI8NytMZEVxle2xdpiFRXRjDBv8z2QLcZ6fblzOiHNrbf9V3fpcnoLzP+1b/6V1/1GI8fP8Y//If/8MN+9ftGvufeAm9Xo3EwEjrMStA6OickJUG9bOCTddbIOKPLtx1AVSUUeSPkI1AvCMU26nxHKAeLOu0B0byt9Eh0ZCkKaSRrbET3ZN3QsrXGkkyRQwn6/+JenWk6nwhV9L20aTu+mhXmcPmwUrR8oZmHmVN/iJxA5cecLjbkqUa9XLOyn/H2FuuHO0JjUZtoizcllXXT3KtB2SRoUPbwzWmHi2nFo+mI222HpQ5N7IcygcRNYeektVwza4u+zBVNGLtUUImxmAd9t8xgbrjaL1g2XfQPru+RWHC/qCFmFpVr3FSBi08q1dkuaveWC780yeHN+F8bX0/7BgBM7zHKpUO0BhcbikMkaDV1QhEQBEtJ6OV2C2vT+JkHgyBh0KJfthsSgtbkVtI60cmIOgDQkhKlvCbfhxtZR7cw7D2mTKd5TDfwrLKDjpB5l5/cAjKnanKz3l/W1K1qZWyDUtsmjLVlHMuE+3VCrYz9VJAMcVpbsrJBjVbzVDFNWs9bK4G+NKse8Tuqp16OGZQb8qya5lLJ+DB93nmqaDWr3nzSXK3Pnd4HOi+xJIByVb6MRa2Uak+7Vb2xvNP30LOMUAerpDrYRBCm+B5yLepFyWrB97D70QMpDcbw/OWysa+0NnLZCzjYST4ZvmrQu2UctMPD9J6K/7dZgogk2Ri7VS2zNhxQKBoNWB9oyQ9BH/JysKbEi3mGvoBYJRpH1RYvegegDgB6blmMpCBkxjU3wGW//L63fkmSBeVawCfC/MWEutPzSXcMOTLwjopOlLVHoo2HSjlSVSYgqzpKs0bQFgUDOOsStK2EDbAyBMJ2nFRQ4y5pWcSFNihwz7EK4dntpRIoWCPdj11qrudityJzw9L647YUFdk4zL1w3mtynTBVWkIRPhNCX1vCF28vAcAIWcaW5IacCBez5npzqig14e40a+cSgpLRXNDcy4CEcPlrGfxexq//bz2Nb8arNJZvUCGD6OxzYqRnGfWKIPuqJTJCvb42SzgLYrlP7RimG7EsQ9KfEEgUrP0bHa18xRuTWL/Z2Lts2/JImoTUCWBRrgcQ0oxnbFseqhxIQCc9b7ksQaJCQ3SpQTb2bKPOjGZTfzLuRhPC7bbD83WPzNos5JA3FOlGZanKkZiyGc4dRUvPWk2h6mOLyg84UWxX0GrCZnAtqiJznFvwRVJukLmiTdpPWIMb3W9oMaEgoBtcn2/gXOQj6mf1h5OgkfFOvPqC1TijkRKeLgs4i6rheQqwEXCfogKjGQoP2yvrToDLrxGM/HU18pAjca9NgOalKF4obm9JR48izfv0hzRBoYsGyIyzpLc0BDzkRAU6US9kJzOgMohbfEChtJAoE/qDRDNeKOM5G34fGQpHnZJC26a5yhtFdQHBDSqsgTOZodEF1RpDNtIichLNCXm0Tej5JYN4ACCR9YjdNH+SFusDmhrESoTESBDLmlFLUqbnTKiiRtIva2kJDWpQHbLOwSSWMLSA5mMbhpytcHzXsmTL+fT6Wze6U6rRvm8lwU3bdVSDJZ74Mb+1e0+Qv3BeMvFmfMTH9QZMUy8jEVUE0hI3CRlG2UmIMsjYNYrVQRamgCuDCAU1lrGcSfciXtWZb0ayGWVII7KO46DvDX4gj7i24TN+SqyGTtNTQHM2r0PNrsjkEbjBy14lQYyzNbg15VQ82J2iYxcAPF/32EzNDdA1l637VtS1G9nx4lLbfS7LpChbblhO/ILEbk9dkaWkKLF1XSPwCtBsDo45MI4keocjQAMFD6BQ0R2YYa6JHYI3ZAKAiNXbbpqOzFPBss69RKohFMLQCJTJDLFOq0xD9P1VxittbPk4RGQfUO/qta5OPFLFJ3QjC8vB5IZ0l6NIHADQAL5LuPx1xukdQfnk2nOse4WG0ok6yYnViHkzcpmMdOPOl8G+kR8OFiC692nRbro3A5PRWXACYCO0veD4DS3yFuWR/n/KmgPibA9uUoLT8X4GsSDtKtqXdpqnfndR+JhSNIB2xqLnMmjS3Mc8V4hUlJsJkgXbwxpNm/WLgOV+QtnUyKZcsZtLFK6/d3/A8y9c4XP7gnlf8A0Pb/Bod8TtOqM2xjsXd5hZ2cX3ZcbT0yGIFac6YWsJD+cj9mkFyoyaCvb7LRboUhLulwlz1j69tTFOMuH5aYetajmUeIlDQIK6KeUbBm/A+ohwmt+U/rxOQzYGX7TQ0237io3MEBnhEuLroENMtBEoaaXCWSkfMJT1KRxcrlovJ3KH/0SgLaFaWUnbWMVxmqeWyCLmdt4T25xhMU1el5l11STPKVMhsBE8CejRrcBIREooBVPPZwJo0iKVwyTKRs4rbrYdvnS8wMcu7nBhXbvu1hmf/9W3IZPg8uN3Fs12Jx8k+rVNvQFnG4tUELdOtiwUvXU9FVWLwfdGcK2VVJveGhJEoNQImGsgb0RQwpKRqkaymQhQNmU1exVJz4tTBDIEoFVW3o8TyszgNm9ssLK23puUnyNze+kWe6/0DsPb8MuQ2zgTpzCokEKMwt+r9aJB+x9QCX2PSqilVd8nZhSjTV42Sbetf5XXrOUTxWKN76voQhA+3u8fqCfmMpMvUOGpmtzbzhRqAFWcmesZpEKGmoogaPFsx+VNo3EOjzBC7/5v/FhJjzEEIehyZ+ZkUDUhcaHwXuesMC6gUac3lvYG0ZlrF7cgJUTNXJCpBnGqSAohdK3hrchco+1XFNk31hpjy/86g3mrSfPNrTdIiHaKPtXmGJU9UC4+4AF7Mz66Q+j9keVYfufrwXKKItT3iLFe+wOPDUWOhrpdJ1WiAVwRm70ToZwVTW44XavZiJBnG4XtQ30/ozNkD0D0+T4T2heK5ggRiFheM1rx2dAyvqaI1ZajeYiTKfnEoEVV2s7U2tANbrMGIUo2w/tIW6FB7JdlaJcKcUjkwcXe73rScctiTt3h6IFS3E8LxGRlU+JC5864E+LTaE5+NH6BXgcSesvE0WKOCMRLjFc6sp1uCIvn35omu9OiJCJYw3cQ1BuNfqZqdOZnhP0Twc3/ydj2zeAF6lBOUTz+2f9thm1l69QBlGs1trxpfdt2aMFQzM8YV/9DcP8u4TRLGLt0Unin7tDZdEkJWSp8oddElZCPeh71GmFU3evVqFzimly4u5ZkbEA9Thu8VmlAA6vc5ETIZLW293r7aa4qVp4akrHyypoUUrOc7vRU893lbaNPF0J+mjA/J9z/XwUPH9xhzjVEJohU5OLdBzdo17fYpYJ92tCEUVrCxbRFf9q1JpzKhAbCg52W/NxtM66nBRd5xWVeMRlJyvWWBeoIoCaFygHsUsX9NmErScudKgX5QkyAXCpArGoy20MJiK8d38DIr9UgMScRaoSOWmnQ5l57qoZW4Vk5JZXyMxIkbfx+JG2oIhCvpW3Q0hooVySdSPu0Hq096KRMZc3nCup1BXZNkaj7pCSrvehObcaRNxWUwTT0cbWuQXVnQcDJoTsK9KwJ0JKRwfK4b+o8FDOkpTGObTKmseqZf+HuEkyXqE1TRvLuCexry5xzMu5EsvT16TTpHlLVyFdS51/WFHNHszZ6OB1Vzq95VOlz6jlzjyI9V0tQaF+o57SHNBi4qXG8y6BF7QKgYkZaApTVAWIJ6L1SRs0N+UbPz1FDSbXvz/uKttOImgDIXe5z/VXGK21sg28jZohgUL17n158bl5jDIIJUlj0KLpQGhB9bN2o9YX3giNL0lvseY1cUrihWc02OUmCLLfqmXXzWIEOK/dyII24zgrUjTWXjlYfbLlqcq+tGFY01AcivRCpA+rRZvPSDbqO3EMjVKjkI1FvT9WMSNXdT5tvg6nE4K3Ect6/lgTJVKJmrpiTilqcasapqk5ytOITVh1l8yy3ljQyzRyt+oBeo7tZ55Fd7uIYwaC0MoSeP5KISsb7785OXP9LFqa/GR+RMS5mXwsWHUZLTDb/2/cTmGNs9Zpkn2lGgupEHUXXvDaWrY5VCKF7HsPQLhWwQcDFZxKt7mCj/67GRnoU7j8sEIxRLwLJo2JELoegPep1518oOmltNWG1sp4mZLZeAsGadgVEiOqGxsr89/1DzjZLHfTCMtQXNbrVSgh0BrhxacSiU4+Ku7gE1FkaxH4CyeThpyHu0zifNOx9Z/e9cKR7zyLWQpA1a6P63O+1B2YvM15pY3t6tyCTYvx8YkjWsh5vHMBLN2g6uWKayIL1LcH6UJnGEFJodibsPq/dd9bH2hw63THqRUO6KGgnhpxsYith9xSgKjh+worck2B7CNzCiqyHnpX5Xp+Dtepn850yE+tlC6iDLTKPLhL2AKRbLTk6fEFweodxsoS8MFTRpiRI1nqx6Xo5e+iJRIvKSwLtlRLf2rA4oR6+Mxbb3LRTThLQVK0pe0K7VAlKPprbajnw9S1BmkZPRrWVMzc8nFUGsg3YTzFD+uTuArUyruYFc6oK/baEu3XuDeuNrMEQHCwqXlvC8WYHzg3XhyVIHfo9hNu7Pcopx4YVBDBnYzJCR5VGI/ySUNCb8REZGxnpiaOjl3MsqNi+MCoRGbwrhwK6y8g3FM728nZTkozlWXlJZjwJfGRMt4Q6A20nKpjghrmRRkUMVBdSMAiaSVAnQT003VvCAJP1z27IJp7vjQo6mdKlDPU7tC0nI90R6I6xPargqw2tahkMHmxISVAKY+EUzT6WkrAsE2pJuLw8YZf1HCcgHF0mwVYZm+VcmRtKTR15yoqq9dIeUb/FDGieK/JUcbrdRXQOaAQpK4M2Fc+RU+oG1Z2MW20nGOVNrJUkYlEtsdUfC2lEy9Ae44AaSIOoHTLmVXPh7dB6TlygAkBHxnTDWB82tOuiUpowrYblNTC2GHIpACJa4VVJAu7MsBmvNqETpBJ67mLw9NoMoElEnn5cIjlnnglhvQbYWYtNrF4NqggFdI8JQD3YKa8GBfu5iBK93CgLA3XGeS6AzEF4aA+NoOeAYZ63EwdsaMce2ENuh/EFC3TPsymsFfmbQmjEKuTf2CTjuNct196Ts5nc28QNxQgSvvim1HCqU5dvrDmYxlOquNitKJVxu+6QrZlANSWaDABJtZUzNxRh3NVZlWxqBk8tVK4SK/RNxnBOuaJNFM+FrNyL+McFJLpIuCDUw96M12jE3jFoos892nMJVznYg2GGl2yPqbNt1A3nJCiWnvpZWasjZhihBl1O0MsShyjJn0uxPKjuSxT7k1S2XtkEyZ35+74xRHHRS9ucheb7nY8hzHYUa2ustbOLbmRs6Z7aCKdV69dzrtqQwKFcIVQA1dI6rRHKaYpKB6QGmirQ2JoWkEH0qmEQhtbPb+RXFAIN6Jp4j/CIZtHXuk+B57TNefHaZM91hyYC7D6SBWdCKE4C9X3CEImyH5BOg1CjIcxLjFfb2CYZYAfpYhBVKeNtAiCa25UEnD7ezp9NJyB58hvA9sC8wBNFTa7Csw2YG+ol4qYf320GzwBErK25ktXtFjrrebm8rdZ//4WElqHN2EXPdfceY/cEOH4cKFctym1doapNWuazvdUL03mza9xpGZD4JuFwUCXtMcstRCoc8qmV47uV5OSqWK5Ek5T5nhravWHis0lVnrhzqfYNfFA4adkySrM53LLWvdrPlCo2CIAJ1/MJF7xi/2DDfZnx3997CyLAg4sTJm7Wq7YG8xFQFarSGM+XPdaacHG5qIEmwZxVZSqxql3t5oKcm+aL1gS6T70V2k5l8jSSF6SnCflIWB63c+3VN+OjP6Ye4fBJWf6yr1a5QMjPk+qdXLI2tDiU0EvH1FCvodwQd3Q9vwutRKBNuRdtEpTrFuQ82ml/5XbU2k25GKQBLaoW5miOLrmBLBqTk4r26N7EaIdB7hHo0bL73ay1vGIpnzpJj9jHx10AaUA1QZrjOuH+NGO9mzFfrri60Ebxa8m4f09VodJlQcoV+90WtfouiOOkKXo6qfDOZYPMAB8EDQ1oCcqaIHXmi+U9GwEPt2B/i11IGhBCAFhNhENc9YmhiMI9m06CBNOaoAGM7PS9fJfUYB4Gtjdr4DM/NU7OW7ZPnFKH5g9VSZQRrABk97rtXm7veLWNrXuaJKFloTkUde2ccddmdBab0fupaC6lpqbiFM6UM+Zg87yoMQebGaizEpI4D/t31aJr3ij66vrf3dstl+oNSVYFmnSvC3J5rDketsbwCn337/H2Uv79kkSVpAqQqhaVSxOcnu80kjsxtssKeijY1qz9arNBK57rSKL1gBUakSe7/qaEC6XgS1w3Wr+20SP36LmZ1zpbA+mlZNRUo6FAtN8DRS73+nCCCGEyJrHDyE9wgbf2R1zPJxyL5niPW9ZWgtRrFF2XuTZCbQpfObwluaHtVMCDNvNoC5uaFJl0p13DS+Zd3oyPyBhqUOuhnXeIEV2vzoxFo949CjiHMgXn+Vogco7lINbj9jzNIoJBoxghI8hFn8MqCOIWgJ6vdETJNd/dGDR3nDsRSCbWdUwt1OeaGSmPKOO8Rcvj2AhXpanUq1ys2O827KaC5/d7bFtCviias51Vyzin2kvs7Hxb072jXVa9NmvC4ukrIqCuSaUrdxWcjaAqRjqqtvdsSkrV+zHMvSCcIgCqKw/jz3i55Mbn4kIWYUt0SxNlGZNYi1OCJIYU/Q7y/bahQ/QCIEMFMQSQqvPKp5fbO15tYwuE8YyNv6m3UbMbJmMA+3y4oVsJvAB1R8pc9lyBHbNNBGoCXgyCNPo8DRPvcKpYyR0WBi8MXoG6x7nUmBn7ctlisZJAFVKuBOvDhnzUaFVhZOkqR/55r6tjzQdJhTKXYVrYjcDPE9JCmJ4RTh8jlEtGOyVlP+4oDLbOhcEgBlkpLKa1w7JBa/F2mpsR87x5s0jaoHKxxcPcUIwR/eDSGMXL3G/TC7lVQNtzvX24j3ztqWTcLTO2LaFsGelxU2NrnYGWbYIIsJsKkuVjmAQ5VaxlxlZS11pmAYt6pLIxtFEm1AM+sZLNDurp0zZQ/d+M12IQoQvNX9QzEpSSmwDA1iATmJsqEzlEG8YZ54bW9hxJ1pAkiDpDBCqwRgTQtneFkY8m31p0sVc4PI2ex7Tza7PtbaeuWsWlI3pqnEytKpEZW6BcaN1whL5elmTRnV9Ga4ycGi52WzSEf1IS6pbw4MERU+6le2QlPi0cAgqxHK+nlS+ovrV4r1sSzSMfGS1rXhezonZxH9a+l0pWg9lMlzocFK/OsG1G92ZDGU76+WZcGgpj2wKFAMRY3nreLavKl5d7xT02EhavjJZUb142ZaenhYD718DY0l0GHgJegwXAEt/d0xQyYwsETOMMtfCCfOEBwSqmCiuZsYXTNAfjmp3BaAO6cokdr+7VIAEwRp30Ams/j0VJSeVSc8z7e0K5UIF/r4fN97pYtgdmoDddFLBcEVWgzrogZa/0dGmEktRZaPsGWXKQg2gzDeC99Wm042nOUnqzhGAo6iYhoteOos2dqRLyLSkJb67RXej2bgaE8PbVPeakAhNTqkjUQpHmSbtAE8Inr57jIq9RR/vW7h63vMP9MiPvGmivMPIXj1dYSkapCeuawtt3r9oZlFtJWNeMw0GlIe+31CXqzBNmQy3yDWG6JZwMAmJT93kzXp+RPj+jfWPrPIbWUyuOgkCA/KWMNgvqx1poDwe6Zfu1s9rF4d5ZAgI9g2sNhhbf7IXCkNZ9t8Re7sInLS10wo5wR7Z4JUXFZl2/LcPaxFFEY76HySRYHgnKVUWaGuqSPpBBm7LuC6UweG5RKy+ifbJTathN5Uz1LXFT9n9N2tJzKmhtjuCFuWG70n7UYhG0NIo+3rxTMmZb0WFd2GXMDduj/jsvGkVWItujNfBQqFyieoRmk6ONFqvSuwf5fTgOps+aSGzXoraCoZr7pgzmFSqerxVzBmgjbNdNy6leYrzSxjatZLkJ+3EjSuhuGvUoLJolG5xxlr/1YmfD9gOTHye4KKbfYN5PiGjAHiZEGZA4PENmKAk9Cm/9BradaCR6q8IKbSdIRRdKOpKVFdilVM10uDdGTRP3MlnOmQBJDCSg7rQAW8Z6QGvD5UQOj5plap2ZKzS0HEN45EoYsc8ZfFIODgsZ3X9RlRaHiFfrfckkmvOpCUcTNG9XFK8TCa6nRUsMzIjuUsXWGPfbFNrIrWn9VQlFGrIieyVZtDVB9qbRWkzf1AQ4qOp8cdNzz8c+F94M/M14fUa+IWxGrJNIETkk20t08j2hbcD2WFMv/qxohy49liRDmzKdO/6jofX/u5Emh4qhhtk7D7E/r+pw8wY9rq3zgFHtOdbG6gjOSmvcyZPmOEsS1KsG7LQOtkoKNm4M7kI3nn8dkSh1mrvC1Ng4hMiCESNMLU5WsfQS72tErVodwFq2NBm50ZyIM81noLcEdPLmKSmhsVmKsEEjcksFOlmJc0OdCCAeGMXjPRjmp5kNSdoyL1DFNuyHhXpvcSCeA6qEdlEhXPAy45U2tuWyIkmOSXThB49SmvWb7d14EBOYVoVwZSLUaVB8soVAVqerzD/Lcxh8ezbInOIkSsDZ1Psi6He1rAn5dlEBot6s3MoMRIDtuqEeNGrkVQvW216jXiU9oDsJjYBi0ZiJZTdYobg/gIDmI5qeoD8YToIKMofD0wKIazv7676ogYBRogpiJ1gOqmRFQHQL2j066duFojMPAGwG4U6p4vJKI899UmHzY5mi80/mhst5xVITbpYZc9bG86FM47fPFmXipmSO+x3qqiIB25a0sH6uaNm1nw0JsHrrcimoB6BaW0ZeARzfRLav0ygPRFGflZGfM+reSj6yoDHCGV7eMcTopML4fPSUi+VO7b1UTK83CZC8jMc29JU7C3kjQNjKzwTYKXwmK4f2eLmqkENFBdC87l9g3X2U8FRZsBJbY4PWDaftbx4p84mVCX1Rtd8roG39BEoeLIR20YKdnVLDYb+BSXBcJ0v/APenHWph3NweABLs9xt204aPXd4hWX2/NjJQIqUUlWnscoqiErFsvWQtim1JwGghkSkX1pN21ZIo78AjlVCvK+rV+TqVJEjWucl1rKNLTyWti00CmRRJ5Dsry/KWrL7HuURnA4T0Pbwv+jyYUUd0hyLIrmoTig9BrHylja1f+JjAJkFEMW2CwriRX/AbZYXfDvM0BISqlHHpBnyYS0kSqb/RMDurWQvPyeTYunGK8yQBWQK+7Sw/ai32qglvUyW0qRlhyWAjk2yjAoviDdawG01A0PuV4NVhdLz8s9Cv5wN+J2c7s86BWA9MMW3WJoR5LiFs0YSiHKhl9fwSqeaqw8fFeujC/wXOcrs+VIYRUY403hSBeboeTIhuGsQNDG10L+ObBVFrDbuXXDX//Wa8PqPO6oB53q157o5s3Vk1gSNdZJvxGXLmfW2HBgWu6AQxFMpVFNDZyrHvEIKsRIYokQliIDdFqYDeCWjU+23S1a6GCLVXQNjesBEkw8iRvjacbOllfNLfbwz/2nR9JhITs9A13jZdf1tSpxZQ3gSZrGsIWjQ6J3axpn6kqaOA5u8BZFC78N60LtHoetAgaGklpEfszeewaXtC+66xF3BIOiadcKr2faORjPRZD7IEsPkaDIFD/3Y9Edy8GJF/mfFKG9v5iwnlkq2QXGGEuhPs7hnppFBQs8VDjbQdXRK0vcIq9RpqFDftc6rRD2tC3mpmm9dmEoBDRZ0E6VkKwQphwfYA8R4qFjHbTa57iZwoBL0uK2kSf/8FRptt8duGXy/MWzW5N4Fqke6/SFgfCrbH5lU1xAbAR+4U96TUddcerceknrN3QbrP3QsHwqDzSrqAhxo0lXUzAfWqm8J2KVqEf0rgU8Jqda9e+7pLBccy4dnzC0xz0XKeVLHniplV//iLxyucSg6t46frBZaScbvscDmvePvBc3zpeKG9cK1F37bflI1sJUW1sRbXX52wlaSykpOSN5gFTazTEkPvqRWwS+71clTUiaE3xva1GnJRQTlDLgtOewIVjSxlX0PK0DdzALoOk6BeSXfapgZMTYUSfClVW/gOiyYBHUo/jrFueWfa4Xc5+qqCgHJhhtA5JE7WMaeeorZTQrPX63Y1ujaHdeGhyYlGntKAVhUB49zQLqo2LNhrOZKng+ZccL/MOJ0mXF0suJg3M8Da7rI0VqGcyrjftKFINsa1S6eeDXNCiLSFHg4b6pY07VMZVQR0VbpXTABf6O/NRUc2Cl32KIXarC92TWjHjPkJox5MrnfSeXclPA9cmnFceiOVbryV7KptTCUR5BKQjTE9T6g7UR6O53ItoOHbBL59uc3jlTa26USo3mB9iMCi1tseUnrBc6EC3XCTRqIQUXEK7wgx5nkBLf1x/c3cAKRQpHpfJDh4PqOM41muxr0qi8LDUxo83rPjwc6JKRaaAHFcl2Ij1mL7OI7ACCB2PJ+qjQAm1fz0OXHx7QZEA2wasOQPcN50Lg2qFYoid8/rwA6RuCGTGkgAaNIbDHgv3KVkrC3Fgs9UNc1tx2ESTKlG+0Q9ToeTJdsmwwNZwTxyoKMO8YIzF2ORvf/63oyP8PDHyDcLwcBV0GiOPOISF0UxAxsRECnLfVeNpNPLAz1y81pXBOKiz2QQpLy8x4g8Y07WpWTP1PoJPVWE/hqZAp1YzShvwzXCHvXqPAb0yMyN0bDMX1zqvm4VYcrIAIp97mSSjrUq96ISRWN2YIj0zyDCjgTEJdi1t8J6uUni0sUCImELJMijXzuc7e3iqGNVwxyGNvgo6OvekcDxnlmkH4+EMY7fd08bFF1sWp2BsSHOVxivtLE9fEnAlwnlUlSC7J6V0LCznNylsvjSbTIlF8115htC3RPqVQ0hjHRSenzbIeAI2L98YtAdo15pw2k3TuVSGxA4xOowtmSNsNsMLZbPDel51jKky3ZWfiMM1INge1DVG3Xja5qbTlxqe8Hx/6has5clDCIdOQQ0gsBhrMk2N+BQTIGFjPYO5Cd624t55LTpQuVFr6M1DmisGkRe9xKazV40DuuKVM1L3M8b9lnZirtUcLhYcZg3PJxPoWu8tozSGI/2RzQhfOHuCmtJOG0Zc654uD+BIbjbdtjZsYp1/7mcN1Qh3Jx6j9owzhYh02DkIbbwmzpXMMgqLUY8SQo91dmayr8Zr83g+wTstHPN/KzLKfY3wBAfZeE7WdHLCCU3TO9l5FvC8f8A6GoDxPKFlo/0Vm95qtY6DghtgHC+1RmXXYn6b1/DctA8a7szJSdHx1p3EByizreMfEtY3tFIm5qKRJC9p61mOKoaByGA9lrG0k5Z9yTL1bI5zdNUkQ2t6qkhrWXfzxtKYzx9foGyJcgpoV4WzLsNdJOR7wnlooBThZgiHZH2295u5zD0WtsrKjtZNYJVFNpa780V5Zi0RJI14vSWoHQo/dqyYHt3AxatGKlJIFNf/ygczehBhLYJ0pEw3WgKQbLm4CUD2yNVkKJbFcSpB2OCb30/hmljpwVoL1nJ8Eob2+1AulG6R2NeoQCdKj/AQEGcmhDQsr+nTdb9YQMY1GvZhgYHZ/lhe5FaF6Koh25EYzRYI+pz587Pt00IaFmFItzjou7BWpTueRYUGBFDuoC5e96ex7VFL4X7woTNj0dxLoLuDvb4zHj0bXPKxkZ2YXAvJ2qGALRG0X4rDmEyjIBGs0wNx6LdRN7aH9WQGizl4hSTwczONC6Nw7M+layQlUHIJyNwpKRELY+mRShUbLTGtl97iJL7P2S1jS/pnb4ZH42hSk1KrKm71PXTfY2TrqtY/xmdZWxVBW0yURQjAcXfbA2nI6HMxmmoKuwAS+1I1UgzPc9KwnlYzFNnOKPZIzMfHvV5yRAvlv8UDbDbLH3929r2Wn+6Tb0M0SLzEM4wI9waBVoEIGReRSja620lqVzjbrVc7UAeld7XFqTX12p6oZVhj6Y9Zwt2o0iBvsmSIFNDygVI0uFfAbCYeM1+UN9KAprVsEc+eOMQv9DGEZ2x3DJAk+khWP3umfSi6P+d7+MoqZd08aoE1TYDrb64sX/weKWN7ekbBO3hCw2aX3QynH1r4v91L1gf1+jWQJbL2660xmp+qlByOaiBzEfzei8sT2B6p2QbN1XC/FS9o7YzoxasZxi0M0g3VpNUtJqwetFzuuJOwDbQ92nQY4a9tjDksmgj6FnZk7zYw5IF3vGIKimL0mvXrNSl7ZpG5w7Bsz1smcIQx8OdBSiE6bkeY3tgRK5FN45ypV5EsehURNvkebRJJCjC5pUznh73uDvucDWtOOQNa0kmhqHvn7libQmbMJaasJaExxdHTFzxhZtLtMZ4fH2H+2XG8fkelBrS1DDNBbupRE/KWhLqyioDZwvHm0e7w+GwU74HcPPb91y+GV//QzWxG7ATlH2LFnu0EgTGHqYG1AQke85H6JWB+lbRijGSaCNHFvXSkjE/I0hmtIes63BhbRPn6nSnhOv/h7BdEu4eSVg3SQLs6uDw2ppekm72WasephuVTm0mw7hNFPWn6aTPd3mrgu8T9r+VsD4UlLcKaLH87l6RHeWyAK32zltjSmZrHGIz62kCseDqsCBxNahXsNl+V1adrzYBWBlVgHQokRJKSVB3VaPRjdBIGcuuFU2XBVIY6WlGPRBw2MCHojWzFoDkZ4pUbh9TdrAzrmF5cGqItoG86l7Km6FYF0Y+nRrKjlAe4CwgI2eQw5BAh48JZ6ph3jRmfVxRd69BzhYwSNMZeibm4NGq0vcpvNPtspN/xD3MwXORLNiu7VeLgutsEafBrQ5fNmseDwHKQd/jeWKZoN/v0C5MopEsL1ShAuN276jqw3HmLDCUzWivSeQ9eh0s2QPgz4P4ogQiIg1D616hzZmg1wnH+4EgVWg6009Qpef8V64A3xPqweZ/UcN2IoHst/COnZm41AyGRPQ6zwUNhLUlZG/RZRExU8NSd3h63COxYD8VJIOgL3YbmiC6i/CsJDBOnQnpDefFEIVAM9xhcUaoEV40QqFQoXkzXo9RLhpIWNntJo5Q92ZQG6zxgK4BQo+4ziUC0VvwOfvYUCRJgvWh6eYWBt8lTM8Z20NCM4YzKqHsoXWyQN/Qkwk1rNwhY0JwSihZidKkqBpuUvTTdmNQZ3Qi0OD8jwhXON+Tfi8bZFxMEnVnSlHNkCIRla10xMoj1tYYZbPo3SRe45qc7xKKc/bdBp/Ha55fHYQkODHKaj23UzMFKg2YSIZrGNCqGOYQUQXGtqnBmXHSq6v0WWAhwNAhrN/PHmHZOU9WEvRyCDKAV93YCnrtE3QCaus3wnOgXM3Le1DDCCmBqcXNkmS1c3sBKjA9V1ZyuW7dm1lMEJsUVqINaoiuWhAcJNmDDqinBABiuqQEY71q5AkheOOEZLlm1+0UkFHd0Y2wPzMBL0swisMLcxELQrCVZTJlFYeN9zoPYs7DmVShP8Dj00uCcilRyE+bFftnABcCvkvgjbBN7hDAit71/8dtilzQlPoC3lrCYdbo1iFhALjfJjy7ucDD63s8HPJIb1/coQpjqwlT0mjWe2r64g9R9NahtlElSxLFohGrk6w7QNb/nQfxzXjlxsNNrYxzHFggF1bv6TXpXtLnNbEucJDRiT8AXH0qNmZTSCpvGzS8MebnjMMXAElaUuN7Qbkw9SgrDZQsQG7gJKgmWdgOZthXAiZonWxmVBPEyXeM7WFDPUjoBbS9hPDDWS9vAM4tcVEIr2DIWdMx3rXLa969x60INI+ba1QRTNxQG2HljLblgHRdlx4GnzcAsrfI3YhiI18RpjvgEDCbXGxZEmhq4KmhmnaEHKrxaihSdDIaXAu8MDVQTSpE5Ok620cpt07kMqfbnfd6N+ncuPNi89QZ4Yg044dpYPJKG9u678YGTTVv8y3p5pmlk/uMGRykh43Vi/H8huVplESl3m25kI7ZOwq705vGq93gQQYSsOi26nGoaPu29YGobKKdpzeSptUFONDzBYDCIovmF6IwfTViwK4FBIqqxAC6U5hYHq9qbEyAmyyiixyrR+YNqkiTRB/wJgqbzSaiFAZdj9HcG/SWhEBosFLVv7VDQztAIW/L2yZumFMNstTzdYe7ZY6odKvp7D1zrphTtdyu5mHFWMotKXN5sgLmzVxiV7zxGsBSFZLWonk2J8dsq0lTOkohjUJmrx5EWyS+Ga/NkFMCgbtDulMVNnFFITfCAJwzgQ0qF3hhjptHnVZrSd42z53OJGE86l5wetyfx3RHQb6pO4nITaNX6/rDOCvDaxZ5EwCwQrVtEuBKwBuQb5I67Czh3AMaGJQLCfg61rNQV04bWf6NsQppn1pbU62RNRtRZ3YtGdlUpYgMXZqalt0saSBk9oDBka6QUSXp790bo9uJmRcmQdkAKYQGdvhOK0IsmPDAB349SWUpYYhnua6gA/UI1P/13LyRp6KDnCBacnr5FYBeVQJYZYMOXhmy9Pd9pfFKG1uZVd1EBmOS77SOsnqROmBwEOBSg1zUGdWD2FtGeINhTeVxBhOIFVVLZdAYrW52EtzfTxUmQmHQtdP/N/+bngdvhAY5IymxKZnol1Icnybq5yTqMeYjq4BHUiPWHGo2ibFxkImVNyMiUNZm8iJqRGUnwbYjcygoUcBbAn3QksmmhcdspQ9eyN5ASFDFqJkrDnnDs2WP02nCPFdM0DwQAOxylzpzuJjQ2wGuNamMo0nDBaxleSUA4XULCWp1WUebPmMhc9H7FUIhAxmi7gRS3hjb12nQyrqewthCN/tBcAFAX28kING+082RIIusPCLTfqgqUAM2BMV4Am0WBZ28AYmJ15crU55zR9Z71TpJa9yh8xBc+Jqcmor4f3FWZqwJ+YwwqbCgzRqR+/U4UepFQQYBgqDYmiqy1aq17c6iruAQrEkuWJMaWtUSvHYy5vPe4HDBsFYRRhKgqISoeyB0b0m1EMTrcExkIvZEJ2XZHqLyuHbfDIYPQYx9NZENu1YnvNl5hAQuBhGOhpDmBRDzFiTS0YEomv9/mfFKG1sAkKP1KzXjsjw2e7mqMYPYZPnNEPXqaCPwkqw0x+rqzmruuhITFX0omgtGNDOYZly5QPWSoZFxAYNmha+bwyN+LBl+CpCPWjoTjaiBaBCvxkDQvGuRyTMKa3s+alDPzzcDFtCuKZw+t97eyhZeWozBuGcImS6se4hAh8wEKgZh5xCtpuxhUxYmBQua9w1pqgHpes52l/QpPJYJc6p4eHXCnFVl6ua0w50QrvcLJm64mheDi7Ue1wUyRkWppWYsJeO3njwAkeBwWDVHaw5Da2w9fIs6Ho1RUwY2Qr5JQWhTzxWaNzdRABlIaG/GR3+c1dkDcElAvsnKIr7SvGg0G2c6ixhlY9B90jadl7UzZht15MzylCFkP6njLYLYm8IBNCTGe+FimTr65spRng92+HOI0tqhYRsIjmcda6DfJwmgyfaDjCALKoKn+uIp6RqulVFKArMgpRJR6fF2DxBwsV9Rm5XhAcipgfcbamUcbybwBlRTl8PKaJmxTFVFNZJoNGnRb7WyOyncnYgRafIInAFQC5Z0RLqw/dpkMWlyyUjuxFlDKni1nrezCpnkO1Y2ckY0nYncuSuDiZKw0nNge9Ag9mw00XQj37xcZPty7/p6HeaVwqJEsEItTkQKRq8ZT1dAElbv8iyCHMpmPmiQM9XIj4WuVSwDCsNqcNssvZ/ti4cVPR6HiASC3YyKYCrH2x118dIE6tGx/mE4z9RUmm1XVfJtKH/S+fDjIIxnFJnHQdALu8cSoOF8mpHA3AinJMhZ8zkAQrQCANaWwCQ4TBsupg2H3BtOO6FJp65fs2uyjtKN3sygruZtk5xFt4CWGzFrbWOeimqrDlC6z30IyVd1qt40j38NB0knSAogVSPXtPa94kViUQgnFI5GAbrHmBFLA3knoif7LHupXl+TUeriurxWOcErnUVyHl0DOG8Y73nRNCi/jWs78sro69yjM8FZw4JWOYiK0csXanydgDh25hGhaBIS9bm5xh7pCIE7uK0mi3L73CBbE5UPiLLPhuW0oxuZX2f8fbgWZ3LW8f5RFzfy/a8Z2hcqcsOcv7glWumo3+vI/fo+8hLjlY5s8z2rGEES0zqlTnYSQnpukPGkUZj2NwTKdUXNgrY3Q30/KkcND2eCGiwiVNMjRqHYrNNJTCLS4KGNjILewHcJ81NCuVSPt1mXDWEBN8b+85pbPr0jceOmG+3fuD7Q8+iOQr9mbdxuHvFO+sJaEyQTUm6DhingLaYAYLsW0EGPQ+OCDegM/YHM5qm7rKHlmh0uc4lDKupB1kyYJ829AkAVxqkkbI1xXCc82C94vL8PcYur/YytJjzcndBA+NzNNfaT9rc9lYzTccbu+oiLaQt4+dmyhwjh7Xdu0AQoVsPnBl4Gp6FWRvMm1MB5Xhx9Tsiuib7SQn8zPnJjfpJQJzMsjj6tjHrZlGVvkaEjPN471lEe2jwt4Zu1Il+BAgHGqtUG6JKBCNYIuP9kC4PAKyGdkkq7PiiQjZCc2WtVDFGfG8pV5lweDdq2pujKvieNtl3SkdSxb34CuYGyAE4gXRmyCrY8ocydZZynitYI65ojrTM9WEJ6sTTGskyKQu223tc2WR7aIlvZa+62bdxre7NEWaF4EwBB7L/Rq9ahc+8ORIh0VeTLfTSACkPuh6g/2otS8HLEaoslC7YHzdTz9PPRZN4gbGHofZ1VCEkMMeSj3tftYUP1et+vMl5pYxt6tmasRpq+DMLTZN5owLcbh3MUeUwYUzXocRrJBo5vJQHO3BVWiUdAooQkpMDe5xX1JgJRVC4WIe767z0E7fkB95LDmXOvkHDeCL6aZU2KK0eR+DCEcSbfGDJmZmxJtGMRbwqjOSEgvFCx+RxPtRGadfgQU4bwnOpSkzWXd5Wn/lBOgwScJ9BdxKKZF+uLfmsp8khEor1yLadUh9dDBB0ICcmetx8idJ9bX6hW9P5mvEaDhn/9/4LoJetlcYqCDdELue65xHoOfoOX/8Tx+t7hx/Xh5T+0ajqICzQXXD/A8RufYYJBzi/83X/GqM+qHVTEwaLqMUoe9hkhhBE/X0/mtFpEmowboukbg77NgPm/Z5FzI0Sb0bj4Yd59b6neFMEu1dNfA6oQl/via5bfjj26sOayQ/ud4prFc+lOFPNUgdgebUxyAJ1Ua2WY476nqQX9/MuSK19pY3tGYHKY1x5sMap36GcmFWTgE+HiNxhpAdIiWB5p03aQ5f1GHdIK8JpCuD482KwC93yPDh+R9NwxMdq+YXmbYoGlk3phbdLjn95WEQ0nYlEjLLkp2cl60fp1pXvuESehW9zhoaOTtoUqLJAlIb+XdYHNpjBFlseuQNlZYf2iouSURdvQbYzLX2dc/c+KL34bY/1YVYalwfXkUI10GJkqwLcZcp9wZEHbb6ahSrg7zdhNBR+/ujWmMaFI0m4i3GXgci742OUdtpbw3ukAJsGj66O20NsmPLlVSbjHD+8wJ6X9MwkudytuTjsspwnzbsNuKjhV7ZdbPaqtA/RjG6ESKgj53qMKoJ1e7YzKm/HhxvpOAR9SwLAAIkoi0aYlaEB5WA2NsuqBTTkV9Wpwys1R4xNBiHp0ZuL524MW5SUBbSY3dg2NCdVSYemLOUpUxCMs1xnOypZ2QRnJAjkI2oWEUEW1dnmwfCXtKuRCsE6ei7Jjm1Fx6DsMHzo5kUhUHMYJTwDmRwuICMuqAjbacF6CsdyJXR2ZQ2EtZ9pXjW6X1AMXOx82Q5eOXeu97VRMRMlMqihFrqLncy/a17fNQDtU0H3CdEPYHpK2APVSSgs+pAz7O4mJgADpBFDTIGy7bioUctG6EX8BCWzX2iiBltTTeV9lvNrGFoDXhBJ1ZpuTGLywOi3oqk3J6kMB9XIAbUI/iZXJDE8d0B9CM4jk+RGWXk/ruRSDOGhFeKfxXJj3qg2fgbKX8P6U6abdPTSoU8OvrDfqD60bCjOecX6AetcbobVs7cCgbaeazo3nJAUI5+D9C1/nbLvg8BLTHfe2Yn4AQpeBM+dDJm2zBQD3qzJDUmraDN6Mb0GK/E6mhkYqeAEoE9nzPiDBeInM1i0EUG3k4x7MDfupnMnLATiXhvMo1yEN6AY4foREiWx4U2f7eg1BN7L+zHjDEM+doiuOuTiKmI5uREfu8A9R4rhfCKTvshGhvvC71YEHnEkeVdlG74xcI1Io2Yk6r8ODDG8w4GTQRmrYWFSPYHzwPQeKHvV5RDquISJRI79mRbEqa0ct299oPKRHtgwlOY3X+WK0bntZ5KyJggOm90HeR3WBIAhXjshFQOXRtF+TX7/dx/eJe/i8+hR6GhFDRDveqxfOQxsiAFiG+/hVxitvbHkzo8nA/JSxew/YrjQful03kADXv8Zom0Ges2B5u0c4uy8mTLcqREFMoCoAd6jI8znkqiYbUGZos+LZ7sQA89BGSCeOBVhNqIJEHYHr/y4oB+DZ/6UPCq3mpQ7eJW2kkbbJKqaTGvhqdb7eYzMgYFGPUKM0tu+FWRKFyAmdlexCIHTHQCKFXAhAFhw/JlgfqPfOi+aWeQO2B1BJShPrroeGdM9IJ0J5WJEerNjtlH18+/QCPDW8+/azKO3ZasJSM67mBTMXZGoowvifzx4CAB5f3oNJcDWtKHKusfzo4hglCffLjPvfuNJ8y9tH66Ci8yFCSo7KFWVL3SsV3SCpqF6tNonQ6LYlVeGhN8b2tRq0MFiSOtn7CspqVNqtChq4aEE6quM63Wh5yvqONS+xRvDhVHsNNxBEGy03g7H87YtNmSoMPcyBvmod+jXuhDeFV1lV0kbz1gpTEqLNpj7fdk7uVDY10OmYUC8a+O1FUytuhJpHeALvYkO7qsRCbpGmmXcbZCacbibwkdEeGH/FHVlIN7iW0km7Cpk1epZKoPusds3zrCTaAi+3+ByOJj15oU5BosGZcGcA0Oj3JoErsL1VrPzJnP3cgJQCcYNJNirUzyFhG7lgL/siWH2yflfbt+5MOUQNdBJlYdBctE3hbX5pvscrbWw9EiWrE60HwSIKPzTrSSuicopxA0aPhRH5EoVpjUlYlVAgCWhuoMxzCp1jy+kEC86MNzUEYaElBATdJoCqnddQ4+tRIw2LLHK6gs5mDO/zhajbRt0Px2bod6cXnFmXI3OH3subjDCQ7hjCLq6u5+dwcXWt5NGDh54/zMBNyXKy5h27oX2+7IM5rPlcnQBvIO/iFZlbPwYQrfq8jdf9aUbZcpRDeHkPoISo5exiEV1EyAUshPocDW/VZ+UrPmpvxkdsyOwpFttIx+iL0Ak79txEfi4EFWz9N9u4CZ3ZbMZUTJMXq6nDmUwq8MLxx+fxg6IkR7+s8iIdbX+Z6TwX7BEbEJB4vdCUUT1mrVJIorlhz0GLr3tAZic3etRqIhSixKBGhhDamgWJbhOC0FHW/6vIRVmzzt3Ioga0LhhqfMm0psVFOJJeSLNWoXwitL3NcdGIViZBdRELBxhIotIkpCodvagm8mPzE+ClOwzWoOGMJS6GYlrAAqDnhKMK5eWMrI9X2tiCu1ESAsplQ7keHnqb8O1a86m0kUK1qRsdZeNJdHAQY6zpA40ue0ZAywT2OlRv1CzQxvVmWKmpulKbncWm+Zp6UOuu0akTLtyQ600NGrmjO1YnqyIc1KEeN5AxD4J2pZXf7TCyMNClGO0hDcfBjLiYW8oLY3pGWB8L2nXVHNBGqpo1I2rh2NqEnW0OSTBNFYdZCVLPc0PKKmZxLBOeHve4mDdc7xY7Lf1wE4pcz1IyJJfoEkSkilGZG75ULnB/mrF86aDXMzWVcGPd7aqp3Egj5KmCWYVHUAjpXjeSdtBN8qyWzqdp6tf3Zrwegw5FjcvoOA9lH7zpa/WigRLQZotSjY3qLduoEtqh9tpRAJKaIkaVwSfCdEuKFg3lfE6qagcYqcoWPXD2bAKA96yWovKN0x1Qbb/SSoh2Vonhe4ckAR5sKkF5lyAHQrrc9DKN6QwA8xNtRLA8VnSoGlScuWFtuj69mbtqQSspEkSaixV3WDRiTnNBSg1lseJVh4o3Bk0NeW6q8ubdeljQpqYEVUPq5CCqCHjD2FKDXGh0SovWFEcFhaN7ZA5T0qYMXuLDZqB50UmtB49k+r2GO1Gu/OXNW6rZiyh/FFBl1So4mEjIh7C3r7SxbZME4QyATjgPAvu+gMwD4gKl4PtVN/VqdCEZrGuBVd2px0grARYlw3K+/lm2qDYtCnk0g5Vl0uPke0aBetHuxZ4ec8DFAEw2bajhck9ZLF8q2gRAogH94BlHkwGBXJmMycbqbLhUnD8MDWCTH2v28DTTBoZtLE4qG9mNLhmpDbXtFMzDCzY1S7TEIxJcXCzRhxYALmYlTW014cn9AWvJuNovEe3m3DBn7QyylKwOaWPcrXN41tNUUR6uWqy+JpDngkmh42XJqDWZghWCRR5s76GJhD4PJufZNOVQXzbx8mZ8JAaR9L0B0Dxg8f6v6BGvQZQb7DXXHvffLT+p680NgK2nrH21JQN13yICBsyRFqg+O3AmDehGnE8q2NOy7UWmy356R1Es70R21lDECUqTBJMaSSAHdVBFCDgmpLsUvIvtgcS5RdkPN+znDcdlwnbK4KlFDTsAtKTXqQaWUVxZ68VcLkHTVkA3isC5kwPABXxCpKL2OYS8//5ASKVvgQ43ewXGaOCNFyMOmFlpVjqxtWF9/7PBi6YOovOZl3NZtEuNtF84AfmWgduXs7ivtrHNYqhDh5IBnBnZ6CMrlkMZo7JG0TigWb9KXvWBrjsJJaoGN7b6Hl8oZDW3vOrmzqUbMaoAHwktq76w91LcHkg3ZkDU5/qxlASgCyZpIIi6R+cz+DAjrxsDII8scvM8ZRYjVfiDa/WxAq0vHoUz3DB55GsLgZrBx8Dw8Pa5U31Wir6bron8wAzpZo2G97mgNMbWGDd3e2zHCfKQMOeikJOJmgOIvpmlcrTf2+82zLlguqrYasLd8z3IYGQ/ndXYkV2aDRHN68blefhhDs2RrXs5K9d7Mz76g5L0sj6oU52Opi5kZCNxQ0FAm9qZoIOnoQQS0VmUBHl5oBEHXTd8RIMCwbJIbuRuKKIF5DtWffWHFggU20MeeQ2tRIR95isOFRJeskN7dcZFNA893RFq1T20XFcgSxhSQBWhLqYNT0RJVjxX5NyNLbOqTK3LpJFu1Uhewth6NIiem/XXxetkh3M2Mqg2aEGgDNbe9wz105JM6Z3Z3CC/UHkw8mBcc1lFQ1i5PsnInRHl2rUthjqYznTco9L3FqoE2Qj5SJDjyxnbD13v8Au/8Av4nu/5Hnzyk58EEeHnfu7nzv5ORB/489M//dPxnt/9u3/3+/7+Uz/1Ux/2VCLnQk1ZvtMzxu7zGXxkM8A9J6owsC4INuYuFzWq27URj0z4wBcbFcLuPcJ0o3R7vmfkex4aSqtKVLEygOv/H2P3RPvf1r2Kf6cTYX6SMD0n5NthoUKNf77V6LVeNY24SUlf6ag9ZPO9Fax7m7+qMmNk3ne9bPrZwpDCoMsCOphy0gAniataZTvGypieJZUxLFpb6985fSljfsqYbjkibi/6FoOg00kXi8pRErYt4enzCzx5dqnIMjdcTso6en7a4X6dcNoydruCw/US7fAeXhzxYL9gs5pZbUqgvWl3U8Fup9B0qQm3d3ucjjPyriDnimWb4qdsCbIklGPGdrQErEfptjiUQKbXIklQ94JyISgXDfXyjbn9Wo6vp30DAOqawHcp+h3zwphuKQyad8uhpE0CRrSHLAcYKZolQY456lQ1ZcVId0mj0VE60QxGs4jZ28mlhfpaK7pHlcuG5e2me5M7wSQKZbujzKaPDDuvhaMJCYRANxlyTGoIK2vpje2FzutwgQl3mktJoX08zwXpsmhzgmXC6TRhXZNnv7q9JIBSA0+W961W4mPMYU6CPGu/6Xoz6ess2hHomFVgw4VzPECA7s9tYHN7gxReOWqH+ahzne64z3eDOjA+R8kcFov0tyu9/nQi5BtGfppBd1nvZToXKwmtbGeKmxgHLXoO7SX5Hh86sr27u8O3f/u340//6T+N7/3e733f3z/3uc+d/f4v/sW/wA/90A/h+77v+85e/8t/+S/jh3/4h+P36+vrD3sqCo8IrGehlvDwBs0zAucR5EARD69SKKBQ92hH90NztwqZ8CZKpCoAGVrhRrORGtXd04aW2eo49W/5yNbY3QhXDt0CBu1a3iVbzsJytFQIaTVHz6DxcB4GEp+35HLJtjw3vbRGEdWKa6s6m6F1+Ltl0U4dlsPVNoIIz5J2+n8BdbF0Pw/voWnfVxZtBN3Le3Thbab0lEhb7E2polrPzItpA0Pw3ukAcMPO6nGJm0JV0Ii5Nq2dhQA7I1iUwgFXhV5sNQjAy5uc3m+bJ2+9NEwSVMxkEkh7Y2y/luPrat8AVAVoIzQBZNb6c948dTpoIntEOhJi/DkyzkXAuC8QH7naOhzzsX4MYyiHjKy13HL5QC7epKCBCiPUjYCItCJNNKSKCADISo7MiWiizrafG2CfcVKQCftH4N0ohGkyN+SpYFuzpnBqQksNsneV/gE29sge0NKgNjgkUEGMAoAWto5A/ZoU2aOOrNmUvcivANC7jVlXoBSVBBTVEpHD9vvCUJjfjzs3bShTGdQsRTbbPTdIW7+Hevs+odg3qFqEPbDQv9r40Mb2M5/5DD7zmc982b+/++67Z7//03/6T/GpT30K3/It33L2+vX19fve++XGsixYliV+f/78uf4nCVpu4JIw3RG2Ky3rCZUUmwyHhJ0QRdYBpiUAkxjMi64bDFt4FXbjVEpRDEYOr9RH0XKS5SGj7s3ADYotwirb6JCIilsIGtuCGnI5ft4g4PgNdo5i3u9pgHvdeJxYa+72LVpdiQC1Jo1enxO2a+2JqR0qdJMRaK2vt9qSSbA+wjm0A90wqFnkb+Qvau6wGIy9MgpyuN+lJlRjFYdmaqrYT709hssw7lPB2pI2Y5AUcPI4TsuEVhmHC20j6KIVZU3gJJjmoiUGS1cGa1fljHkukyDfMPafB47vEuqldl5JJ0IpStR6M75243di3wC+/N7hIjAkAN+rE6fpJIkyQqrA/QOtU+Vba9C+a8j3jP0XCNuVEm7O+B5uBGAOvq9nT2+MxsQDATNU+ZYwPzNi5oRIPcnUEF2Fignu+zgjSiIi51GOlVcCnmZFyOaGfK9onbJ2JdYtsbb5qxtjzTmc5JwbRCq2mvHWf9Aw7vn/V5uFtI01ok29PrdsWQ3U3PTfjVE9Z9q0pJFPDH6mLQY9MocA+RkDrD3C9f2Ac3EwATXBggFSKV0AVbTJyvRcJRWLSE/J7WhQzVJ2sx5P/90etg7/A9bQRv87P2W0SbCFIIgEc3l+kpDvCetD7fX9MuNDw8gfZvzWb/0W/vk//+f4oR/6off97ad+6qfw9ttv4w/8gT+An/7pn0YpX75P0U/+5E/i4cOH8fON3/iN+gdLhIdgQ0JXXxoeZp9osnyAG16HC5yk5B5mFw5HQAS8dUMcN5/Ov6PNiEXn7xWyc3S2cunnoQup32R/v9PQvR40jJt/VXOigHnC3qfWF29jtC1FDuPsvIe16T1qlZVs0Fa2OfEOJdT3CgCdQDL+Hsos6iEvJeF+m1AkhehEYgmJxiaEiSv2qd9zZ9dXofP0k+V3RAiJjRTV+mvaCoz6fY0fGu4pDec7RLsjNPgmsP26Gb9d+wbw5fcOXij4B9Gf2tEt6pGpt2Y7W0cNfR373935bP194iILL67dFyNSWMDVgLTKuYgMYKiU2OehXYXqsCjtHM5E9Cs6ygME6SrWhcSfdO+o48koKuYlQF7WA6jSUjohanZDyAL6r+uytzV1hMmdct+j/JzOFjr1dSjD/joORpCs3lcCOexH434Xc1MR3BRtTm/nZBC69/ql5gfxY/lnh+8hxPMgSb52ke2HGT/zMz+D6+vr98FGf+7P/Tl8x3d8Bx4/fox/9+/+HX7iJ34Cn/vc5/DX//pf/8Dj/MRP/AR+/Md/PH5//vw5vvEbvxF0TEBS1tjpnWbCBUY2sgJmTa7r6/levc56Yc0BLhq8birdsOZNNqAll+xSg5iPhOkGZ8pNnjugSgEvlwt9j8K/pDZ/Aiqr90sNmCxvS5fqSVcm5DtGviGsj0Tzr+ODYKIWIGC70lXofTP9YRACZNLaty11uUY09byF9PrrVQ3oxklDVBWubhloe1F4raoH6V4cgMgZ80o65z4PFeAjQ5jBHzshpYab37rCzdxCWjEnbQy/SwU3ywVO64R9LkBWiLiB8Phwj7UlZSCTKHu5JKwlIeUGloZkmqzbYqpTWdmV25IjOo8evp6Xfq5RS5uU1X3zzUDLKj5eD5q3lVlQlzfW9utl/HbtG8CX3zuu/hvj9tsEVBjTjdbB1h0iOlwfSK+nt00VQMgInj7uPA+JyoBmzH035G22TXvjrrl81L2pWbWDHlSrHMql4Ji00bw62i1gT3XmlRS0+3xSrsHjAm+jmaw5SD2ow5DuteqhuhysOdTaQAHYroytXAi0JiNyeSgO6+iTwpCWTfO+T77NrokQ2sho0FKelbUb0pHBhVAfFU1xGUFKHPqu2rTBm8gAAN/r3JbLTmyKFqfGAnZSmvNEvHyKN53v4ydq8E/qhZZdptsEvmPQpvvZ9riCNsL8HgMzoTpKKBxOl0bbguUtlc9NR41w276ZTrbyaAqMT/OSvbC/psb27/29v4cf+IEfwH5/XsQ4Pvzf9m3fhnme8Wf+zJ/BT/7kT2K3273vOLvd7gNfjxAoGewywif2gIp02NN/In9rDDiBDJCPHdO8pzYBzToHQfTGUlH1IWc6kxnsOC164RxHLxLm8J2sANu/csjj0qZOQuXzz41Rs3huoaNFaqCXpGSuBdEdKI7tNHax00q68LnQWYOErlsqfS78wnySknv2/X3MDTlXrKyLsQ4TwWZAEwtSalEq5HKNF9MKtIStJGtU7ccUiKhKzdiODwSw9d2Uql60ZJ+Yfs6OWjgaEd1/hojW0Yc34+tj/HbtG8CX3zvS0iOnSO27UL/l4cQ2VjH4EMAZS3Zk7eOF9d2ZxraWJmge1aMjRtTWe6mBkHIoWsb7KgU8JxyRt71GA3o1ngfBosik/4mMrB3HyZi+5kXQ2dnGYq6eu21KvkShKCni5sYTveGH9O8ggdXy6smSCd2crbWB/SwmZhElSK7MNW6AFTFXgDn+473zpgJA7HUy7AMuyQhWcRsCukbCuP5FDUcQ2HyfL3qvlJyqDpOTTV9mfM2M7b/9t/8W//W//lf843/8j7/qe7/zO78TpRT8t//23/Ct3/qtL/8l/tBCYRY6sYlSG+vWIFKyVlJ900UnDbm3ZCUubK3w4uHOKq8oCcg3GuECbDKM+j4nNHDRiNDhZABhzKrBE23WUqH9FwXLW4TtkeV9ZssfnZTRzFWLzJuTkMZIclNVLG+BJ17u04D0NCMtwHRHWB9opBwOyLgJAOo5N2XwMVGn2RvpQDaXm7NNoXVd1kYSusI1A8gqbLGfN8hbRwDAsuWzvrRMgrf2R5QdY6sJt9uM+2W2MoNVX7vbY95tYAKmXDGh4rhqc4F1y+o8WdnPfrfheJxRVwbtKviioT3ZgU/m2SbB9qAqCjHA9A4TpVVz0Ovu5TzTN+NrP/5f2TcA5JPEWmhZn3NXeQIJ2s5JSVBt8bmds5AFxl+gruxX5dxhZ2hJ0YmC6ChG4PGONm4wgnxjhjYMhxGnxrxlObyfyUwbwJUsTWLfT0NEbpBqVCfYeu+EICjvgQVshn4t2fgRBDkl8EnnhJgUJhZofbCvKetNK0XLJakQRBiYNC/KScCoWp7ohEboZ9thQJYEYcAoIa493yWkBdiu9ZznZ3oNp3frmZIWDfMvSfPw0aDB5qQ8aEi3jN2XGNsDrUpwCUcuUMfH9hCItjGcvHUfQSPwSTA9UeGNl3rmXupd/wvj7/7dv4s/+Af/IL7927/9q773l3/5l8HM+PjHP/6hvkNyZ9Cd5WgbmcaxezSiqkVmQHkFJBNqqCu5ApQZSvOswhP1w85AAdSoLYRykB4xMfX6vME4OuPVR90rZLRW1Vo9y59I/x55MW8jtrChD5pLTNYL0bvoLQWbXsf6QFQtJTcIuOdzzBtH67W9rguqRfawOmGPEMWgbP0+Ltb1ZKeLKZ0I1UqwQoDCe9p6dx9vRGCQcRNCtchWWY+I9nq1MGpmNAHmpPW3JenDvJymiGzJDXhqUbZAMA83Ucy/e6Ow+8ZN7/2YZ0l3DGxvCFJfD+P/jX0DUKTKmbJejRBr3ZxsajjP1WFAQkz0X9oQrTbS6M33AM8/kiFSGw3vVXjUDW3wSMJJ70Y9UjgWNBA0CnVotU2CvA78DZGI9gAg2PgbBeSqakg2F1ZaGACWnVNrpOvRIDbXiRdXb6oqLKHOASxqNHiaydjRFOtRrBY3qgZiDvp67LrSiP3U36fQPM4RyrFjSdNza5Nd88qxp/k8kIuSGN+n7vXzvPW0wLhfxPd6Ttf2abHrbDOAl3TWP7Sxvb29xa/8yq/E77/2a7+GX/7lX8bjx4/xTd/0TQA0L/JP/sk/wV/7a3/tfZ//7Gc/i1/8xV/Epz71KVxfX+Ozn/0sfuzHfgx/8k/+Sbz11lsf7mSmFsbAW8AJGbGhmjHMJryQ1UDwZnlTAtqeIy8gk6BadEiA9jZMvV0WRCPQcimY32OkE1D2HiGrt9isSFqZhLrAWrZZtu/ZrgQkgnJB8dB6ftnv8XZtljGiWerQjD08Xi/aJn1QaWrKsJOEOgvaw6IRYG5oC7pCzUDJT9ZWrlxI5J7rQdAuarTsUugc2L1HsTghyvxOK5Bvge0KVoalBvQwb2hCOK4T0Dgaym8tdaPaerOBZnDysmXIklAtxzNxwyFvavM3wd26Vzm4nbb1YlZGJM8q0UjmXbddiw0tHdXz9q4q6dSRBLFrmZ9BG06/GV+z8XW1b0CRISoEsGikmCU0tz2PKCJBXNQXEJUGddeV6txQpzsNnaorO0WpjjmmRfOxsDxv9FEd1nXU02+kKJtA84oA8h2FkdE9ypXrBPk2K/diVQJi89aaluKijZBWraVXBjW6KMRl6z1cDRpuxKhVUIuRnbJAcu3s5ZWjQqJaYxZiASfdR12cA+bcQoDmZA93JIxLQ015NGAEj4QarEWoIYfWza3MGujo3mcowEACA2uemjbl4IRmgl0Xn3xT1eO3hwJerAxyb/K6lqcPSNqcibozAaKNzNkyjs1AIPtK40Mb21/6pV/Cpz71qfjd8yg/+IM/iL//9/8+AOBnf/ZnISL4E3/iT7zv87vdDj/7sz+Lv/gX/yKWZcE3f/M348d+7MfO8jEvPazcgzcjDVlOow1MNr1R+n/xDhwukXhShacognYHRfSGtmR504ENTE2/p7lHRXrTEWLW+lmHK/tCUnypM511wc13FKxopOEhRfdM3YHI9xpFqpav/c2uJbp5eAeMyfKeEcnqv2RlRN4BBySoezqLrM/y1u5xZ3UepjuBZCOSZSWFabMCwbpk1KLGtYkWtpP1u6xCqCXjtGlJwd3NHq0wDtcLplyxVI0s0+WGPFU13KIt+I7rhLVk5LlGZNsaYS0ZrXEU4/tGoSUTOo/zU3Ws1kfqQKWFoqzCIfM32shf+/F1tW8AWK9NczwT5NDAJyVJblbbOpIlSAjY8OX7lhq61XYSDp6vf0eKeBvYzEAPDszwKglS4C1AJUuUIfl6rLsBAbNo2dvqlYshreXUBRqQHbI9ywhUmv5C8FyEoHWnrCIezr/QNdxPnFiMhWwErL1FvKZ50Ko6MJIRUbt3FYKTRRrUQE7OgaEwlIoa6AWK5bW9mD7KMlfjmYzBCOy7vBKEND3wYpoNougAG2EMxoOJaNcck74X2n1yxT2GGtoKJVUtBLxkL+wPbWy/67u+Sz2+rzB+5Ed+BD/yIz/ygX/7ju/4Dvz7f//vP+zXfvBohLQyeFWvrx4sv5q70aKiuTlAH3ohNRIkMHFqr7OlgFpdkYomQdv1v/n6E4LqJbP/GLySu3Fv3vey4QzK8IdEkiAVYH4GrQ0z/ePI/9vxAGhPyUpIR0BIvePmBtr0T8WiX68BzlaD5q/T4K3xSTeabIId1bSb9eLsX+r/+pzxqsa2zmSkKs9d6MS1Y0ZLgnKxWENpFTRPJCrXWBnHZca2ZuCLO+SNUA4bUmpYSwpdZf/qrWrp0LJlbFvCNGuZx7JMkMbYNmVLMhmE7TfHr6ER9k8U2diu9DlIK1ArUAf5t7YTzSO9GV+z8XW1b0Dr29NKlkdt4NuM+ak90zDRhcBVNdI8I0KNOR7btNuu6fq/c3jXjy+QojwM93+9UqLtBLC1KGQ1nntBZa1HHZuwt70ziykqLDCroWsXDW3WpgejNnBwFUxToJpuuyJZ/TjCGsVLBnhS8mGyn1HWkln3SxfUaAercGCdEzG0QCfZAwxLyfl0tUFox5wD3iggYXUU5Awi9ly4No5RZz9kbCud7ZvUTNxiatGr2w/iJV1pkG/tezgBIl3+MpwSUoKbGW1JiHw6LwTqZdxfcbzS2shkuUQIoVwofu5iEkpO0BtRjXyUVjMc3vjcPZk2LCboZNa9GmbvFjFCw927HG6knxPUoFITiJMXqolXsPWmZaDt9BjuHIzHSYuedwGMOegwhv59uiOUC6AaySJITwTIZdVWWiS9FZZ5ZelWKfni17jT7yUYImDRa7pNZ5sKW+2xMHB6zGizksXqhUTeuouKk5brpIbdrqimcapYSsZxmUEkmHcblm/Q6DSJSj1mVm/6wjoHAZrHXbYcJQbrMgXRWKDF8+d0bVtxbNe8a7j7ZO5CF5Ngu9RFrX2QYRAcIb2BkV+rUfdqoLy+sk0u2yoASRe5tzylQ7puDMDSCT4y/JB1lrFBAm30wWJKcdINMPQ4bVbkJTpxWYnqyH4F7PFuamyiCUjyv4l1qDFex9DMJN5r5+rGpRwMnKtKzHTj33JDY472lcSi+VYhFKvx1T1Deh3tyufQKxDIHypZtyBEyo+XoXaZEFUTfOSIJCMPbgZSrM+45tgRxpg2bTwfClrN0nfjPXKWs11/uZTYB9lqpnkDGjj2vnBKFt2rvH/wiFC0naB9FSfSxyttbJ3NJxmojt8744wEaNwjxGZeCBv2buQHlz90I+rwi8MgZF5iS+f7+lc6J/eGCGrgqQK1kPZgXe38bJEoc9lgUIdFXLJx119TAQw7ZxPY8PPVDwGUtF+lt8GSMMTQPFFV1iJMa7UN+WiwbixsRIuznq9DdF4u9KW0mGfpvKKAjFThiQhmaLUnbROVV5ymipQaHlwpY/n2fodmJQYMYDa5RgGwlqTRrQlYVGthlgzWaraIiTGIiQ8LlQXbg2YLyRCFnS4yb5EIV6Q5vcS9fTM+MqNlgJwBK/p73XfHlwoQxB2HGIFetuLo7IAIkac4Zl2YvqdQsVSRO9WGbPmmLmaIowzPj/fCGifuryssLLF3vIhEObLHm6nZDQRJL3XxCgg0sg5m9tmm5T61Ms7siEC5H1EiZPNR1CihDLwOQvBdzkQ6bC55UwQwSnLMAegtRs06+/X6vgrbiwc+o5PGQrQo9isJqcsgRA6Ot1elkHCUb3Lp5UKOIGjULTjrEoV+nFZfB2NLajgjP7sR0gYtlh6uzBdFvtfF5Elzb4zObtyaGb/hge7qUvYgzt1rDPEMexi6+gmiXrUc7BwMzigX3trNr0GCCQ1YJL5X4+SLwhdc3feHj6pC59sVILmpWDoBUljzJmv30Jz0Uffn0EyZEYsNJCaArnnN7UqiKF+L/M3LMxnLtPSNxsuC9DqBVhmSGmbL126Wj50mzQFtW8Kj6yPmpF18HApOrA3nFXJOWEvG6TRpKz7WPpitMcrdBLCAd7qyRYB2SsY+tPMYVMDOwmFRkZK0AtulRhXbA5PFfDNem0EN0YaSFl1k9WAGau2lYq7C5IIVAOCwcrCHSQ0t33OoCvneQYuRiPbQVMVKIKuMoEqYnxt0bQhRPIe26MkZ9EA/B3uWoyMZ0KHmPLwHxup1hu+m63fzSgX4njZcGwvklFBPCZWtGJUEvK/gqaEa0TI+sRGosPFf9FjzlxLSCVjeab2TmEe4xpXwJiDpnkOpi4g6T8XndTMHxiJVIYT6k5+HWA6VDRWoHsA07WdNFSi2j6eTkVmzog1e9jnW2orxdPJdd556vb7+35tG1ItBSOerjFfb2KJHVoHXi260Y5EyYfib3yT3ymT86bmFMLZj7ZZDITS8JuoFe1mM5wH8i73bRMBPQ5QN2DmQBKGHLMq0XD4iyeO/W6Td64bHC1K4B+W80Fp7ZqrBFWM/nzkSzlhsbjjRv9Mix6hbFhfCgEFG5vH5dQt6qzvo/1czqKo6o14zkzanZtL2dltN1jKvP7itaS5aEnrLLsCk6vziEOUEZxAW+jW44+P/d2clvmcaYLY347UYETG6Iz3wPDyCAiwqY+oRpHRVOudM6OvoKabBaPgxzp45P0bTvQPcfUFvin7eo1YDPYyPqNiatbUcyJLvM/2rrB7etADMWQ60yhCgMY1FhcI4BkFpV8GkIjxn59FsvykESoLGol3LLIUXkul+Mpa68/aDqmg33hg7/rg327y82HtW/P22OUcN8aj0Z/BwCGL4vA0tWcMWxDn48RD75Ivf3SVz8dLjlTa2Yt5oOqmwdtS5Mno+oHWC1PJYb8QICYciU1bP07WI+Wj5igI1huZRcfHvtkjTIuN0UqEKza0StkuNYgM2sn/bpOd7+LyyestBz7fugfkpIR+B5ZEYc7pH0Hoy+uCkxaLfGZGzwa3KM/JocGyRNyaI5yIImG712taHCrHme0JaVPO07jSf7MY0olvA6tIE6Ug4fKGhzqyRNZM6CHslJJARlo6r1sVuW1K41yn60HzsZuU/y2lC/eIOd9cF73zTvb5WspKrpoq6Jcg69d3Be3UWhhy1TWC5rsBVgRzT0BoLIWOXreeksObUtmvEnAbK8Wa8NoOqknlcFKICvXkI2Tp3A2kGFND/c9FnynOHrk1OALykBNDPi60Z3rRheTWZRucIbA87nCn2LE43GlWVKwn0DRgiOjO+An2+cbTaWTsOAG2zJ4TtWgJWbRlg62yTVoWriS3bZgQhdyTaJJBZkG6S7klJgIsCOqVYW+osdMdBmEDEPUjx+WOok79pkJHvVeSnwtvkQde1wdFi0VFEmgDO+DGLfr9YFQTECJ93QAGhWHogHCfXQkZPnZGLlbARrgpif6yHFx8WBO+FreTJ7QYvrCjiS4xX2tgCiAkac4zukZBPoKAbYjr/rEdzHyh8/WIU7GVDHsn5MUr/Ts/5vngMd9jcY20TRb5ChvNmaxUIElRrMXeeF7L/WmODs8jcjnF2vjx++ehl+kZCIcoxMvM6NN4p9up5D/PcdONxUQtloVkjbQGOR8Wpk20ArVmONTU0gUHIdj6sG0gRNcJrSZozcpIXLIIVhBMitvB7Vw85U4sKQttA8OophI4kyIv3/c34yA9nsXrZCAk0BWEbq+frJDtco2vSIca0mrqaITtBrgRivcXz5eiYR5NyvqbVgA5OpK/Fca3KeNy+b7Cxc71MqIF0fZRuOP16x6YtsIDVeR29WqFHpOB2DrnCPk+W420UJTQhlDFEeh50ii1PsbpiP4exWctZWZQA0uwrY+/2i0dcF2VAPAIVdGWuuBHo6KMb8XFO2/lPfOzFyhP0Y0SjGjsuV0C2l9tAXm1jS+bZEbA+VJEF9VIIUjX/SKJ5WP2PraWtb7wcdbgG/Ywdkdm9XfVWPa/i0RKgn5/u9P+nty26trywQ7MOiwgB2PSBvf9d3VD2/oh606fnQM6kkTjbNdrfWu6iDG2WiOLa3p4W01UWaKRJFwWysdL6YQZtL51uT3a8HVAuEefLG5nakj3gThRjLf1Zr/V78g2hfFwgF8aCToJ5LliWjPbrF6jXFY+/6Qnulhmn44zdfsOcC7aasGzKeMxTxfTuHXKuuN8m3J52uL/boW0MFJVipNwgd/q48mVBu8/Yfy5rw4h3NoW81oR0dFH2zuIMJR9nmds9JTFY/QWG4Zvx0R8yCfK95R89FbVS1FKme2vQMYlVPVCsPV41+qwz0GaKGtowaEnraqc7ZTnXvZb+iBsmglZINEK+VVSo7rRErSZfj74/WK/dShDjlXgP7LZr4I0x3QKuYOfNUNQQaLmgNx4gO54bLb14xN7CS18LzYQq5HFDAZBcQGinBljuUid/7XRvjHSNryeDjF0NyrvrlKv+nWh0Zti8d3c66bwqEVMJZKrwhJCnlKxk0HQitCRY3hqU8KyMJ4yq9SHvbHLEPhffb38PBGGYIzb1rUBC/b0LAafXwdgC8ZDTcL3CziijHsE1Qu5VJdrlxiAFTXj7+90Ns+MXy1uI4fw2wbxCYQzpEx8NDvzcpBsvsu92WKi5lxURaTfy1KAJfzOG6YTwyigp7BPeMPzh6deiuWEZIF17ky8sO7eRyRxzZ859sC2LOShVH2j1eBUqDzFz2DwUpQU392AniY4fmRumuah84+D+emTLdv5rSVjXjHbM6ulHGRMh3SY958sShK+Af22hizHHWaQfu+nGeSbb5sxFsZrqN6U/r98IEuQQDcnw+rCWx0oBQA1tOKFARFzSPErU9RbVDS5YM0RNIE0lhewgLL9ox+t1oRRCDOMeEXKOvpeQO+19rcexjTXs+u3ix8AQ1Y0VCONysD2EQPE9sd9l22tjj+zz5fufG9s6VnjYvHjJDmBxTjaDa3nvQACddFqVhc3otbW8AJhIOxz5fbR/02IGe7YpGRpKEIc/ozbA5pedw2IQ+FmUTMOc2v74snnbV97YRq7E/u/1omAAq/29AKkC6Qh4jq7sAaAbkP2X1IBuV+9/+Kk5hKQw6HSjRejrQ/R6VSAYxbFoCeHl7d5Tz+/4jmuF9oeUxoJ3e4DQ1MhSBeZnJsxgeUaPmnlFNCMIiTkXMd/XbtRMsFzniAz2JmUhjjCJkTVcCzTEPZo+iC0T2s6i/Es1tl4+oIZWz3/b6US064J0UAhgP2+43K2qjyyE4vDWQKQqBh2vdzPSs4T6VsF0saGWBFkZ+89rPuj+bQJNDdtbNSAzGCNaJlFnxATeSQAUYLrVXNxm3rg7FBBg9wSg5y+5Yt6Mj8Tw5SnoGzk16LNkm34bHomoW130/dsDi6KcjGmbPhEg20BcsiiqJQBzl1mtxnCts0Q0rHKiNCBjiP2Li1VTGL8jiD+CXmFBg7FGf2+bVI2KzfC4w69RWs/3+lqO1IyXD1oQIi+SNbNJM7pTYpEq0CeXqqIEkpXDorlr0prjWYDVztn3HS+JFAssrG2mJD0vbnpN1aIsXoHpViP61UWErCGDiO7VLsTjrQu9qkKAjl4ykG4o5khZ5WZLgCGXPQQ0JKFO+DLjlTa2owoKF52IOtLYhwejAYCJTvsEpkVhoJa0S9DooThcELk+0vfzqp5WuUCPkByaGCAZyNnhUHf2EFrexOGSMQ+g0m7DOZicWjlQN/4rMJXe2UiyRYcmSi5TC2adVIZsCEPEK4V6CqBEKJ8n3oD5RsUyyl6QihEaSncCPLfCq/YGVkEOfR8xQfZNF2A1cllWtvFWGUxAJcFp804i3GuBoflcZlFS1L6gXhN4p5rH230GLYzVySQDCYw2JSzogpR+D4Y8OsicqGxEKfc7DCKve6jyzZvx2owR2dGNlHq044/CADuqahCiHaWwOeInjhykk/AgbrTUYFAZ9gSPQAVnNayBKLmjDgTByCPP7dLem3UPc+6Bp77O8sPF8rn3tsc5opb1y6iaMERskhi8D/TXDEE7a9FnMC+AiNYhqr1MWz8PF/AJZ8IjxmZ76UZq5Kd+jZ5jHut1z4ZfJ7oefd3jfP9msb2TrWMbRW/y8f475O0XLgnR6ABApAQDFdj0fc0cKLH5DP38rzJeaWMLl2NcgPlGsDyi6OIwJsDDGzEPsM3KCE5HhCZxQKLUjSxXfWibaSqnI2G+0ZrTutfvVbJTN0QOm/jxIri08wpIx87R23Q55DPqn6ZF3+dCEoAbfDUetDNGpEA9cgawq534UEi7XJhDkk76wKSTnkOBn4cunvmZkSEuDA1YEeVMzdWmqr4+3WqkX3dG8xdGfVDAc1XhcgBs4uSl9iLW02lSdrEQiEQFKkiCPJW5Yb/fsJlUHADwfUK6J2yPq8LSA0xHC5lUJ9AOgMPlrtzlcM/6QDfHfI/YQGkmy+OeVx+8GR/9QQ199/O8vcGdQTy2DTXIPy7aYEScdMuWE1VLmY9A4JI2uGiu9cyI2ZpzazuWnni3MSGFM9mrKmAqdLbPxLmZmA9veh0ekebNyJZH3T/o8nx/4U3lbT2/7CWNYttIpJ3MUQ/I2iPwBcb30O9ly/mmU5+7dNJjlsvurHjkyYvur+tDzU8nR6KcsDZAzT5X9IJNk6SGru7JGsrbZ9hSfZvmv+uh79Hu1ETZYjGDSqqFrzrrJqVpEW/A1c7tYasWgTk+L1nJ8Eob27QSDl9UA7E+NO9tILvw9oLha33Cz1hmBqVIU9gBBCwPLVg0Y+1RUjvTRNZDuND4dKcwSND1h0jXoW2nnJ81Pmg4q9EVN2onNWhyMRwPAJfeccS7BjkbmHNDKwy6zRrJLhYF2wNB4g+/Cjm4lwmLoCF9kcR1A5E3YWuysD5QQzuquzjbkHKDVEK9zag5oVUOSLsZu5icyk9KcmBnMC+Tkh5Sz+1GTsquF4C29zpx3B9ADa9H7w7vtMk3F73O6VZQd+YkHG0+Ls693jfjoz94c0YtTOEJZ7nbYMxaBBQddApAmTrMOKH3r5bubAdKJbZmHAq1/cmFLwgwUXvdE5SQ1R3taHcJnGm6S5LO3RBfA7amRCAnvSZ3kqcbghjyNz/XQOP0jhG81m64A5EbS22As5aUQib1aExod+Al94YeJMO6rACjN2xvswCzOri+NwvUuZieW8Ts+d2odSWDw4f9gDQ15Hu4vrfD+678FHs16fmS3V8qKoIkxt8Jg2xqUV7iNd3ptZQ9IofrELx+7jWIbKlqRLtdKhMYzgC2B9A1L4M9ZhDEGTThr0FfTyex/AV1WJK60ekRsN1o93xhn91rlDUaWpIe0dLWz+mM7ND6e/x4umgNJvIHDDiDlqihw1EEZdw1NURpVShnSwBmdRW9PljhHdH3GiOvzfa9pr0qUzfEI4wNmDLWC/MIg8ZcS5VOCTI1FE7qMQ4Ojpf6uNvotblly+BUMc9NyYTBtKAeHQjBpegA95opmJpcejQwPitucCONsOrmqdfycgvmzfhoDNrUAJAJPbRZiUORMhnIdPovmTgE0BwSZiU4RdnN7DXd/iX26G4GxAxqdBiIfQQozGTfSwZZek2uG9mz2tVRzlCUNBmsao98pRv8fNJ+7VpXqnnM9aGyr6koqlQHslf8Oxi2cf22XQOvqimeFr3m7coM6bCUqCkiSBgCFt/nrLZ4hLDzvX7Vdqn7n+fINXXXIfyz85NhXphijkdkyx0p9m5LrMY9LXY/27kghiMIaVXOzHalqnrwqfB+u7uXd9RfaWMrDBzf4RDQ9+JwF8Que5sY907diFnXCHavhvsiO73j5TuDRqbD0eZV+b+ez9TuHgrteuTri8BvTHZyli0CJzIIwcp4EC8otAwsj/TBGB84Nxgjm1bVW/QJqccEVOtnOZmwBgCqFI0a4kF0+DoLmmFnLzKUR3ayz3kMh7I8byFQuciFQRtjek5oc9JFTnLO7LvQydvuVXrx8uFJc7mnpESs1r9IZkGh1lmegKnbaFOG+Zku9HJpeReS8GCjWB22YC3/Tc0iWruP2RW93ozXYuR7AlsUFkbK6u1pMLTpqE583ff2mOFYJqBBzmpUQYjUysVvaN/q7cojJvTab4MxPXpKp/MoOSKyBLBtTv4st7mr0nlkztL1j6kBaUM4EmMTEy6KbNVdb8jhDVrep4A3oFYRfuYWzi7E0zBWtnQQ1FnOy2nMuScxIQ0zfC5kwZ56M1KZC0pIUjnZ9YEjYH3unZUczU9s/87Wycfr7lV+s8+3G9DIXR+M9Grnyt56dEHsGS0Bd79L7286UkTBXXHv5f30V9rYgrr2cER4Hi1ZpCiiD17Q1T3abIOXOkSZbcbANhsiULM6CqdKRLthzDFEvcODhuGGCEF71pIubGckB+XeouAx1xy5AvPG3lcP6gbX21iZ8LZG08ZMtp6RXkfMq8FgA+zix4+pHb7nzPvEC68zgtEJ0VpCWhi8WIchF97wyXdj6XNaXzhoJQgxPKXikW8o9Zg34IiBw+1lr/c87pHppZ4VqHNPA/jvkgA+4UOxCt+MV384+XBMKQVk6aiUR6EOHztzF8PezwA1M7jDaxAgL56+GRxZeWFPsf0hec9ti6ya7wmGoJGdcxznfcaHQEaf9hST700iwzVa0ECuoudaAAa9wsqC4gNuWMkcZv/ONsxfBpA1LSUJgLGkYz4yrFE8LB/uIT8CpXMS2ZgnlzQEIej7oqMBY3082fGVm2PwbtIqFJ0P6QQ0twVJHZeRpOoR+Linl0tlck93VjZlpz/ygl5mvNLG1m+Ka34CUGOydGhISCn5+h5BORDWt5xKr5RwDPlM9iiS0YkAI0uYEAsrjLYtFBfUzndOudccYT4Cy+PuSUYUPmkE6jKQIQFmkW2UFLnndtR6sfJxlXlsuw7DpEUZg7Lp8fINYXsgKO9s6p5ZFxNqWuqST0qqKBeE+0/4ivUw1tmCw1wYzHXmxQ12FADoxKBCuPgNbet1fLeh7Rv4arMi8/7Rdsx63lcFnKpuCGPUKgw6Js05e7ssh/KGsp5yENz9LuhiqrqwhXSBeLMG3xSasThDNcYW2HQjkLuXdE/fjI/EqAfoujenmzb9f91pbjPqJx3evNP1u12akRhgX43SJMrk3FG++4RaZrYNn6qc7RlK1lT/M0SI/DG0fQ0bReQ8W59cZdgOECz0eFy95SiwPVC/21nJ+aQ5R0qdnORlNtW6i0U6ywxoLYz8NGG6M3nYDNQLXXv5ljuJKHcyETVguqWQftWoukO/ZHyKNitMLqoyq+TNoduYl/rk0s/L6+rTieLeUNXSn3QU7J4JTm8z7r9BetrOSh1dZpdd91mks40t4Jju9L1OIptuAez8PglqsT655lC43XnZSoZX2tgCffMPyNbKgLwU6MwDHB8mjyiHYwDdwLi28qgWguG7wqOU/vqL5wPoQ81Fn4wzeLnBiBHds/Mcoj8YZ6IRQPfG8hC99cvTt3gjAbz/2hU6Ny/bPdnRK3shej3z+sdjjt75+OXuJfsmNAswNXAStAZtkkDDcQBw0vIer7FFI4Qwunne8Op7/65hzn3BuGcb5z7C3aL5Ga/ji3vkXrKc3cI34zUY4UT6+jPHq03nka0/a9rrFKH25iIvNJBvIk3S+vGB/h3sUdyw5kbU5ewhHM8BON9/qr7AI4Q9/M05ImLM2oCXx2jMokyPJBFoG8KxjXN3nWhD0M7OaxhRAnTSgEMYWqu8e/97Iy31wvW+OC/vQwI8T117zfIYxcd6fmGfGBuPjMeNr/R9zvZAofe/X/9VBIHG833JzePVN7ZOgKL+EKUTkFalhAsQeVlJZA3T9W/LIwrSAqDHyHe60deZgiqvC0fCAAPQBUUAjdCuQdejuozmRPyOdwPJxR8ICvLO4fOC3U1F2TPqRAb5UJQulT2C7Vipe5IQazUIZSq2CTh9Q1UI1xo1a/MAQloE95/Qa9s9oahPo2o6p7ZRFMtnOaN7urNzODgq4Au6e9oQPd7dN1UtEThUpEmVo9Y1oy0JYJNYuyhgbkhJUCthe7rX3NNKaIcGPhS0PaFmNdgAwDc5UIGAxwxuYiFtyuCLzSJcbw49P9f8WXkE0EmNr9/3ciBUenF1vRkf5SEmlkClk6S4iNak+oYLK3/blFC0XaiwTDJIsRxMnMHWosugTrc98vLUBS+aJ873AFXBdqn5P08RxQZvUXOqFAZTsjL166HvFdgAkq7326wEJS2+hnstsP89qhxWTb1sibrTjR5YyOwetQSq1yadMze6L7b7TEZYpA24/I2G3bOG208mlEtSeUbq69IbtAQfZHAoxjlwR9rXMkgC6icBLv6HHuf0DqHuCOWgvBSXW3TGN8hy7zRwWBq06fymjO06D0xnOyevzdU5UwY3Z6Al6kTbDzLMX2a80sbWIYnxYYrhD4Kz+aptsON72ODS0ss/3PimRW9ytZzB+GDwAG34ebw48QEnJTXccU7+YLlHRv14bQK2A6sUYoLmaoabGhGxGUeHpcYHhIsFqwahRE0qe2Rnqlmj1+1OhOjnxmYD+qb3f0c6aQlN27uTY44LmbiEC57j/DhoWtOnYhykbfScDCW6UGRH7//c+OOON/kF9Gs5I44EOQI9XzaUMrFBh2/Gazg8UqL+zEQ0Oe4T9hi3gCXt5cGZDhTF/vX9xtfUmBNWx516RDlGcBjWmZ0DDSGtcyQip+j7yYAWeZrEESxVwEOsW49yW+4oE4/EL/j1C5AkSmJ6HfB4kn0uRsSrTRRExCAl+fXbPtZ5JfY3u56u62zHluF6eWiK4qm9AaEMvYNiIIN0FM+bGnChbrgtcJEE8Eje9O+OiL/fD58Dl3Z0h/5lxittbHnV0p+6sxpRG2eQit0Ucu1LQhAIAGD/JcH+vYrn35RRroC6V093954m55e3tEEzXKFEFCJJqwQL2Q2zR4MArGWdHWPHwfbzh8xhzTF/eHpMqsg05G7jYZK+cKg6I9lqi9lZdyrw0HbqBXNR782FzssFgSc919goWmffOXlizGuCDHq1J0WFIQT7pw3HtxnbTNFiUBsp2wSI9qJtrAYVACg1yJKA4jKZDa0lzdVODagJvAJ1aNxNG0W7QY+eyfSrX4SKox6S1ZPltZcSNG8tZjn4Omu0kRaBpA61vRmvx1AGP/T5nrvD6A5ZEHNsMy2XutbYtZGtDaXqrVPkLfV4yptId53r4evWGwW0yVSmxKMw+74XHfIKsEWwLsozOgb+GQDG/EXkMTUKlkD0eAV41X2gXnbDl6xUSTw95fvk3NAODVUY3RGhXmbjUOyk+0syIYnlEWF9kDQiNglFzyfTBEjStZk2nQ+tJUbA+CQALd1IayRu+W2rd5Vs5Z523jBHO61Auu/ReNvB1Kv0vPO97mdtR7GPupfjpC8X5vB7541gRunGfKdIyPI20D4osPiA8UobWxBQ9vqgj/kIGQxUGLPWSVRjnWrdA+sDBldBvreIktV4+8MilufzyFKhIeremRtDhz6C7UpIq4CqhrABf5oBGwlH/rex3m70pEbIxs+dnfeUCQhFF4mojQ1CrjtRlawXlE7arMd1cgJvAlyqcfZShvlG/+8qVq7H2jLpjxX7p5WUsGWRMRVCejahHhq2twRtS73vo8+PsTH1NYHkpgQMErT7rAo9J8LGgEwtFHy0RAOIfr9NpfLynRJfWu7XFJHICN8bSz3KHpJAtpdbMG/GR2OkBZChVtzhynGfcKQrSDukDtoID9NgeBhWB+pRb4UiSpvzJRDRZ7J60OnW+IsXOFvvVPvmnhb9d7vW4zUjcOWtn2OgNkMkTr5PmcMgzfYKnEdnIT04mSEySJW499hNJwq2byBdNgdeeuNjNEpcgN17/RxACEJpnQAXD5FxP5RuQH0/d7JrlFjJoLA3clfsvKIZfAMIVvZjn2foPSEzoH5v6s72ZS8JG9GHAeoO4SJYBchL1v68+sb2yv5vD1vAD9lYqG5sDfpEI9C+z892RSh7wnQnSCfB+sBEs6/6gxfDHlCt5dTjkShMHJGiE5hsQSaLngD7WwKQKAxdJOQHeKhZzjeuq3UvNSJbV31J2vg6FT3v7Vqz/rxSdLxok+astT6vR/Vlb0Xbz5WZnE9aZuBapVSBwxcbqAHPv8mYlfaQVtNbldwNMF1YtNA0d3z5P9XDPe4yaGXNJ1uLuyjP8qg3N2DXVLVrZaSbhPk9VvWWzKiXFo0Mm5s7WVQJ062iFOsDQp0RYuLU9Jr9mnhTz11YrzefVIFMBnLVm/HRH9MtsL6lKkwMk+ozI+bPuCQ1CJHGsXr5ugPaHvb8IgiZFQBxlw5U5SSEYUiLGAu4C+/MzwR1ViRK0L8nLQD2eg7TrS7Y7co74Rhys1mbPyf9DY64O9bjWj4jIBVfIz1/rG3sJNrrMQGw8kFeGOmkOc9RfKfu5Pz4btip57sPX2ioO8LdJ3StZ2Mql4N06N2Y4e58R+rP9tQymVGsQKt+D00y1hFF6U5QkNPsmB7MOJSe7Fzb7I1lBMePKYpWdh0qCOdLunFuk6bQPLB4LQhS0UC5KCQRUWXWyGXMs3D1qEa0N6R7Z2bM0iK6YPZAEwo4I506CSGfupcJnDs0VIDpZPT4Iee4XZqQAkNzsE1ATSEXlQSzzT6/sCBIIR8QUJNGdPmIqGXz1lNnEXUDvD8kNb3WujPh7xN173SAX13oAXtdzLwJDp9HdPVZr+jsWiUDlRQGlsGzPzt3e7hPbxtxa6hR1oMAWFnXpnUFktXdSECyoF4IFga2a42Yo++leeI657rh5KORwt6myNu44IhuPl3ecsxxew77LHf2ZrwWQyOaDht7E/SQcPQ8pucFDS2a7kQd2KNCs67uBPQ9CELW3cZISkn5FeDh2bM9RcmFiJQNNWja5+DHOjcUDUN5kX23t4+MKBfn0XmsXQsSvPywmSZwnxPdb5TZT2jRTQtQLsb/v71vi7msqtb85pxrrb3/a1VBXaAQUPu0BxElNi1YMfpEIAQfvCU8+G7E4iQKMTbpjuh5ODz2gzHaT2LSMSoPpqOJJAQC3opjxNitogRMEdCqooCq+uu/7L0uc45+GGPMOXcVh7rAT9VPzS8pqPr3+tdelznH9RtjJFkQ2b6Q59elSgSF5lU39tjkuWr+VmSSPhM3QSxHSvtW7l9DuHnqyHDKT79fj43vdgDcgEhAGxbk2vT9Uua5mvSclOmt58vTfLYXUSY59zTeM7vpN8DWVrZqcYqy9E1KygOILzIWpouHawZw8bYm5wPB9YDrAvreQZt5x02Xe6kTSrkTsY4MAdYT6g1iFjGR5D4NM6J1AWvoRjwufYEmEDwMrCc5J99ArDsjwHhiD3lkMGg+QlqxmQFcGyiLSO+VDLj8JiB2zdKyhXyR+SZ55PNHgbnjARvOguYMhvm08IDMoJFnraVW0ds0YMVmgX45pJaXQPy7CUbcAMAsiNc/aIiZuEuNAUITEMjAdJYHLSSDk99bxhJkSzk9Z91I+aY9tWQrD/kXXFrgOs4U7TiVBJiXinCUSoa9T6RfuSW029I0LgCpnMbMho21CU6eGlJvOXpIQX4UJDepJCuRMSr4c5kQ9594f2RT0wXtBpWXGUV2vpQYBvGcY5g0k5fGGwRv436NsvYURQvw57aXSJXuzUzxDcsiI7t0HcYDLtun1ZRlnNV2ixKRgkWs/gPSM9TQch7ijfu+AkzHIf9mlWA9YWNkU+WFRAH0OvO0YyRC6XeG9NxtB1hJN+Qe/Nmp2i2ubA1mm+hr7aluojycoOxf10sZyJyJeRJyBsYH2I5QTSgSj9RSbE4QFl726JYs0/0raVCho7Q85za6RVZo9RqfP77EzFqLYR4LaQxu4Hr+Xv1O1+rYqmRIGJJJP1KGw7T89JqrDbDHF0eWqEJOA6s5DyN5pwx5PtM3Bu2yRb1OQj4zsANh+eAUw5zDif/ccAi5SZumXmNrf7oTCLlXYOQ/Fkx2kk2sXjc5cC5XC10JYnob6HxeZTcbIBlAqjRl6tNp7GmoEcDzJuN8Y8lLUxa+ViGVzy4teOfDj4CmywxwzwI+NEww1K5ynNMHvOT9+gUTy/Fi/tGkYyFKxQTEUXih5ohRqp4ghFEquznVI1TloXX3mneNnJNcqWUkqNxTi+RKl+4x77tOlZIsZZ83Jnp/ruP9HQYmKJo+jTIl7Z/eG1AgwMh+FmNEQ/AAUumMOAT1GmJpZIwGtPxZc5K5Lb2kBd2UZYRvADgTn7EaQgaIdfUmK/kDIaUOiXiiVzBwU4JV2ahRtky5kuPIoWtTG9coazJYD5A+21k/5IzY0soWQAyL5g0sZsIQwMyDMYFQTTUEIwI3s2jtkOrTyDETuZ4QRsdahGbMIdfcSs1Ckzolxw7c89R6blSux8xYYQQEy+Fj9IDTDeOSp0hODE6vHqiBC8RTf0R5ac7AdZxvdWokGMBobR2QFpXlhWwohUFybxiGN0M1kXNa/n99+ATc8jzMe3m3xRrfwOerplmoVlowkgUMiL1StRCVdahmshTSa7E8vwaK1mUMLRuKlT7a+1oJUDEd8Dreqxo4+hxi0b8UpkdLuXi4lxTIYWYoiPUUu84FB+7Zm8kRbTSjXIVQp3BsTGtIKZ6CUz4y7caz0arrN4UzCYTZwRnJmOTv0NKbSMQSeaBh5FiqAxM5KyZIm8fI8aB4LapcXMv3XE+0s5XlTaKywHObV92zs94sy0+yafSdhro14jczbMFn0UfJd5t4jxT5KPoddiCWETMvbVau5yVF+nn0SFXhOwBO3x9FYirZWblMxsAMImMak/3OKbJBowsuvfdLgyCFZDXNCFlZxLaaDfMM85wnGJ/wIOvgs7DjMDYg5+Ji5NwsL4BhZHD8uvmZGjjOFSJ6kNGhrIB2m5WcBACiFLrJwh025nf5u6ope3fUGf47gHbZRM+LhM0cGqCX+ttqksZ2jY/zA5h6try9zp9twIp/UEOAi84NAWt7ebWosqw3KOYxhzmDfoHJRiYYnPivV8SFaj2YYdnxBpo75lGvDTjxT2OYOY02sDI13jKRY0yxLVzs+BQMfG9ggkVzzCI2EdFxZGqcqDIdWGjpO9ZQnWuFKJKvAwlT5+PzNBxUtQTXEdply89/ymGsgksHJEallZrMQNJbWJSZGui6dqp1zORSyQJG9s0wNpEbonssVEx6AhAb29hOOCGVSYLcSDN/Kc2pN3TBc87XdUDXMIFLPWe9Lm0yg7FJ6Snt+WyTN6geNTfxgMx/TedY320RaokSVVLCB8BOuBrAtcmwrSZmxuur1kz04N00kUY1nRQce4IxeqDcGZucJDIG7XZINJLvvVtmQ8VHT5pLDm0nUcwqGfyjExQrRPS8WiapMltDyPrcjU8KUnWAvptKWl7yh4isc0CNEKT2tQGZt/bG2NLKlrK/RKbuKSEWhcbz9QGZwN1j2EuU0+gizsKzynrl+ltmE7qOkkDXC1EPV2jhyobVTlF5Ul6vJ/1JmzzIXcVCcb0PK56vMVI3ls7P/5eSg4FnxWq4Vqdp5EQmbh+ZW+0kjErOOQNILSEtK81uMSMShWTV6z0FJU/I4uPIsEnefHQ/9YXovRm5Vv48Wv65hZqFkOL7zAwXMxCMM3Fay2llYMbMnMsEJp/FDURsnBVcwjCIvYJzQaueXqyrH2XyJY+cYNajir9/SrRFFZzNSs0IEt3REGnGMcllSxxE4Ga/gywiEzkaqPn+yP6egywTHZVsGfkpUnfspgauMzEtF4eqmHQ+lln8szxNxk4QwUoTm5gWI0pRLJuuT8PgkZvkUhlmnlKznqMQwczKI0NguRf4vk7bzzT7HOKEI2i0jVNmzAZPXjZZwFhNX7EVEe/nFJF2JmxpZasLrWqJWYIdk4j6eSvlOJTq5ORhBwd0SyyVm5OEquUQhiqgyYJjL6nO8gS6AGRRbjvYoz7ZY/2qMb8gyxuhWQvcarExAHFiHjCxSJzESgKSQtcNpA0yAKBbSH2UbQc064RhZNAt6wtH9DKX/u7hJh7TnTW8MpSNKOGNzKNWqy4A7Xb+oqh8hUXZLVie66n3jpQ/joYKSfhpXUhJY4PVqyuQqWJzgDA63WDQ9nGqjP08vxA75YbmwzzxMboi1TpGMhhCDRhQnEVKmocXNiZsEphc36xrJClWbTdpe14ftjczxkLBpQHbM0GHiS+cqx3mTWwuH/uSazRkA9yMfmySvShKUUv7lK3az6tHKzOv1YurRKkYPp/1FOVUaLKRbZ7XJedqKRr3tfQb7peMNLsQxevY63OtlgfxcA0YYJAmMCoXgOTd8RxnExs0gISL4bgBRb2WyJPRMYhD7ZM8y5tohAqxfpfn+sqgeXEmjOSJ1anRfaqjBVXekig4PZcJLJe0LtcOlOqWhSgVO2FJuDi4RDrVfLcfcRRr/ugAP2IOTjUhuDagX6j4XmUIS73B0cd2O7PJbcccGCsPkpAZN2eBra1ssxsleUF58/7Y5cSmY2J4nZCxfzOrT63IjIWcW6ccNuY5rXHX5dYjUSw7yWECshh/sthya1gXoBoIsS2kp9jEPM/5quVFlY0lQbFWV73fIQu5+Fkv3oiVGGuTM4IFlygJSSMkjxf6ewNbxABiiRUr9qwdpOScc2++WrewndQ4ClFCrXZyBiGSpdKcyWjpZx5F3sUmWvp6TO55+GTB5uxjQ2kmZV4yUXBpIA4FEKGtckOjRIAQmFR25JUNAm1IHwdgqCz5j6Ik2Y/JIrYT5HMBWmNqPUAD780owzxQbwSEyjBRktig9I2JfWHyUkb9vniN+jPx3CxlstKwd53vRd1z2v51xmuXe9ZWuKfdpsrZ3H4lNj6iU5FHuAwSU7lK+9QQgFNk6QzD2szec2yHqSmoQNErz0loqisoM4JMRitWJyTlc9Plcl9qIXcKH+dssaWVrUEKn2pT8LwVow4A0BBFbGwwINWrSomOerdVSwjeQJuLz0wOAgACpjsc2uWkbHUWJXu0XIsH6EsVxSlhy1Cn4nUgKTvjCWFkI0EDkGv1qYenaxEbY2gOtl+w6OfZwzTEXjBZzjPzeQO6Zc6/1mt8rcGxUlIlzi0LEYcfmMBjAW3PeVwTCH5k08LMlG00SghoTspzmDPSEg0IlShVYQ4vvUCYf8Xj6H+p0O3g+JvpgfGrnEfqtuvmSD1Mo+JV8gXE8lzj7+7nTXqv2bNl65o1sPds6WoNXswdGeLGJsWzvaRgBsAN7A02awFkLfzYcEXCNEViOmECaztY1ybjTYd0aArLj3j/z4zlNEn5qOFsjNToqsEsysZ69kZtj5iyMoHYQxsI84em8PMVJjtHcB2PlOsWuCY+ETRF9oiy0kYQLCf5Xqzsq9iDXZi5FKNCiMQv47leVaFeZDUl6bMu95i3eJXvjxwNuf7RyYBuyaLdoRYMYnvaxUMerguYXF5xIxGHWE2gVSZ5+RGQ5K3rWKlWLefPhzkeuOI6GSXqxUO3Jubj222WWeUNYuWI5q1dl/SKklZJXmKzRqjX+D50MEx0os6ALa1sZzzbTEEZteiiBcQr2hI/RBOIC5OR4vWsDCmFNcTqsz5ZQNWEP9dEvG+EqDTVREUiWfjGpM5SniJhwU0xq7Rk2oj1BD/wcVbuTTvOKGKOlXRDpHtUb5qyzR1/z8+SK9QrdkP2+30KwfOG59rjxNzTk/PP1EBpVhGL+622mnQGEAKGBQ+Qtx2Hboc5YHK5Y8LDGudqjRfFHMsUTGqraFPOSM+vc36j992mtWAaMCu7lQ0jz12HOkQvXvJmxgPdUgrhF1wi0LSOQyI4iSD2deY9qUdk0u/kxD3uFpc4AZExLMZxqFkB2F6GyTcm1sECWUWAJ+lexWvWSHQJJN9hDfptTWyYk9fH6/1o+mgmP6n7QvkkeV2wF8Wrx0udsJbBaVtIfS4Ah6dTdJDgdLZ0SPspNu9g24G711XsGPgm55Co8FZ5a7M2thL+9UAwEPY04ujUmfpgeVe+Tt667nWy/PtByofUWNKpbjG4IB6/AeIQGGuy1JcYEkGbAOXe+1na6Vtb2Qo4lGpg46zDLOwK3S9SMqO5B2H42j6gmgZUUw8jwpkqg2HOQvOuoTLwNTB/tEfz2gTTPfMYFhwXpBugWQ0AEUJtOQ/YBbSX1ehr9nLtQLET0/hEYIt5ycIOkmfuAodYxLsK0i2p3gjRGwZmrVMe/k5RIVVTXtlBSU0QwaAbUFiCeaikmiTPv5oS6tUBQA1ylhm7rbYlS0ZEJERVBs1aQL3G9ce+MbMlCVLHGuR47mAFdNt4JFa1AYxf481BFXfa4usykWWsJQ/sZWceeJNCXm4KNOuB35sRVrklNOsBJhC6BZuYmXLfAF9/vRZghoCNXc3rhsMK3rlQb8ULwx+QNecM4FJtu67pyE6WkiEtEYzKIXC9uR5ve0Jz0nND/spya9BJwDBiLRH7+s5JSHjKxm3VUvI2IYpBiDsbu6p4LVwxkHFAjIEBRSM81GlCju4VqhF5FTGPGXOiBBcbZpjY8L+aJkUNAuZf87A9YbrDSRqGorLVP0E8U4jXx1UUBtMd+pzZ+HYdIit6GFvOLeetFn0yPgCOQNTrARu7qqxBBUXDnLtxZXPDRXbnjOJ6PSDUBtPtVshaiLJBSa2hYQUd+9n7FNL3Dbf3ddLCkS/07NbclhYxpjNYPOzjw6smhHrCZCJ9GYAoq0xRqGVWKfnHsEJBxYuCrIFrE3WP8zYGw7wDMAc/xxYY50dJ2oYZ+MZGb0otInKQmlLERW3Ew3Ydodrws3Vqck4A8CNW+GoF5mHketWjXu3RbW8iuYCsAali7nmhDdrSLCTSUCw614XowGG0pgZZJgboJg+VbFplG0vY2bVBZlNaYf+xotN2lTo9KJYuSS7FdVpMn4RAHOig3oOQneKUoyyvmvd2ZiOE0BkraQBJHUTBaOK7iMo2pP9zaMrGZ19wCYG0Nh2x3ARArE6I9aoDRaYte0lM6qnXJF+acUT8yEA4kbCOjc9Q6Vxq2c8AEFLkTMlPUTYEsBxyosj0cm0W0fGpHzHzGE45hyo/IJ4jenxZvaz13OBFo16qKPOymuAAGiX+SLdgI1kp57rkctX2AIbMOMlyyFbKZqLhrzJAok/arlFTRGw86zG8n+uNgKo16IV4pdFGNjwIToyJkJV+Ri5LZaQ3NaFeB8bHPMsrbTxCwGSHBTLP2Q6n5H712YlhcrbY0srW9sD8oQmGxRrDuEE9IdRrHr6uYv4EkI4lAQhZ7kHbM+aEIVgTFVCsF7OIPUH7eZ01ywtACVbMkuOwsXWsl9S6Uo8rEqLk+7ifMyvbUFvOXWgLxyGzaMlIwwglRPCirFd71K+tw48dyGlCgyKLz/WIii92r8nyS7x55V6kqwvmeSBDvREwjE1kN5NRhS157WlAc6xDd1kTa4o5Z4XYXUqt8xlla6UWr0sWpyHE9m8GyRsnK+0xhQQCNSbUiDFqFfMmq9cl/z0kDz56tNn7iBvcaxRDFkRRtpcWSD1ZAA0Qa/OFjWyIo0hR6WpqSTovNauBw6Kj1MpwGCOuL7LA4EWwB/GYZaiJ9Sl8rCxZvSZtRhEZwHEta0QnU7QeOqCLrzELGauSVX6Keroz5T+igGLHOsh+iqFcUbxQZcvj+eI+ktQOKRlSCIoqY0KN2MtZr8949d6z1I1Gk2XPmoFlkG8M+vlUQ6w1+vWG3oQDicFiKI1HjRHNzBDSzlaqgNXLnTu8jmFphGHOSfUIMN1mZ9OSPj3TXOHmacyzwTllqh588EF85CMfwdLSEnbv3o1PfepTePbZZ2eOmU6n2L9/Py6//HIsLi7is5/9LF5++eWZY1588UXceeedmJ+fx+7du/HVr34VwzDgXEEVsLF3Dv1CJVN7AhBoVugiDRAwlP4wiciin7foFyyGBYdhzkmXFYN+yXF4VIhBeU40xukzD0tLkFxHWd1qOkanfqgVVU1Y0XfbavTLDv2iQ73qsXCoZUUvL1UJTBxO4XMZAkLjEBZG8GOHUBu4LsBNSbz1zLsHYpcYzU/5ERsGuuBjW0tCDNMOYzuTawJkI9by2VLNVruEerRuUENryROleP+j4/z3OHuYsnxvD54vO0WcX6lDEkg7Ycl71RSBlx6yIP5O3xj0CxbdouX8TRaKU4ZiJeHBPDSvTQcKNg8Xm+wAshCwrKsUcaHUREZrPYVfoevEj5n0U68HKZtJgtkOQLNGWHphgvFxP6NU6glJ4wpel9WEJ0+pN53Xf2uExnV8jGs5/KrfUbXc5rVZlbB0SMbnIFEp11EMeY5XApZf6DA6GZI36VKEyXUUyygjidSc4rzJPeo+VRkbCVmDpHpExpDj/sT1OkUjeRglj5Mch22Hsc4I5uM0v+vaRPLyjUG3aNEtOvQLLhr0w5zwY0TmxioOyv4titFJS97mJL9zv9ig21ah3eEw3VGh3c5CM48A6rPiSEYi22qu/2wV7jkp2yeffBL79+/HU089hUcffRR93+O2227D+vp6POYrX/kKfvrTn+Lhhx/Gk08+iUOHDuEzn/lM/Nx7jzvvvBNd1+E3v/kNvv/97+Ohhx7C17/+9XO5FAAAOYrepmtDJBqpslNLhP+tqwLR8uS+pdqCzUSlyTkEE8NEbBGqC5YWYAzHSvJdGc3aZ9V6iiFhJ4QjDWnaLimeYWSZPdwFuLU2GgoxD+JpJqSkLL7QsKINMhWIFQfFMYBRkIgVTOK5a3gXQNxwM7R4l3Kpruecst5HEGPEN5Z7Sst1xudrs/Pa9JyUMMLWZXYf6vWrsJF8reZStJ4PyKxM2QjqNeelFqHWLlRIXqy8b0CukyQ/Tklw5SUdBW89LjbZYQjQntox6pN5RXE/SGQqVg0osUnCw9U0JFIm5WudUK1M4aa8sNRw1j2KeCwl5eDptL2upUWnKRJNLfVi4PuUL9ZoFUeB9JxAtRHQHF2Pxnz8jqD3R0KUVHmRPYdM4Wro1vWnyyXe0ymap8aC6yiSzWIDf0rXqx6n3p+ONnQ9Rc9SKyZYkWuky0TDOsnMPKye9jZHBVLVCUcr2KHq5zjllqfdctkF9fLt7DM+tzVH598655VXXsHu3bvx5JNP4hOf+ARWVlawa9cu/OAHP8DnPvc5AMBf//pXvP/978eBAwfw0Y9+FD//+c/xyU9+EocOHcKePXsAAN/97nfxta99Da+88gqapjnte9q2Rdum7vknT57E1Vdfjf/03/4Ne//k4sMcvTqBe/kE/J7t6JdHGBYcbwrikGH+ILVvqcKJReklNOlHgOYYqilbsLog1CtUxhxT7JkSTpVJoSUo681gdNJHBQvL+RtdOPoCxycC3CTAj5kR7CYhetP8HQHDnMMwx+Seauox2cke5ugEU+ftEOBHDu32ir3dSUC37NDP27h52PsGmpMefmyxvsdGZeg63nDtMh+/+5dHYTam2PjAlegXHefGW8JoJUSDZHQywHYBJ6+tMcynMHLIuu1UEy7k56EFQrxSzzULMc8dC+iWDNodJm4WLoXg5wMA08t4gkdopNXiOmHxyIDRay1W/mke7TaL5qQIopbJIpPLDKoJMF7xGEYWoQaWXmpRrbQ4+b5lTOoW//d//3esrKxgeXn5fLdEwVniQsuO6/7l39DQGG5KGK2SGKVZQxwtEdnOSlXnOgOSnqkNmvUA1xJHUhoebGJ7YPmFDrAGw7zs8cZgfMyjWekw3TVi8iUAzQcCEnXZCGhOtJjsGWO6w8VqhGGcFP6piEaqeNftNhsdCB0yULWEetVj7u+roBf+ju6j1+HktU0kWc692sMEQqgshjmHyeUO/aI20UEMudtBKjJaYP7lHjAcSUoGPO/l8XGPahLQL7L8HUaJs5K4G0zmapdM6twUCONjsm+nIUbStLKDnxNJ2i555Vaa2vjRKTlhJE+ZhBCrvQiqljB+tcfopeNY/+edWLvKwU3T8erJ1huEpedW0V82xurVTSRL+ZpJZKvvATozwYv3/48zyo43lbNdWVkBAFx22WUAgKeffhp93+PWW2+Nx1x33XW45ppr4oY5cOAAPvjBD8bNAgC333477r77bvz5z3/Ghz/84dO+58EHH8Q3v/nN034e2in81HL+zRlUk3WE1ePAQgVyA4KpI/mBKsC7RFAgP0uMIM+WFxEvGi+H+gBgINip54kgzsAbw1NjSK0lgHqC7TxCsBiqRGzyYGUbJgMwEKCLurII1mDw3P4LAWgNwTkCiedmNwYQAb5h5pxrA7x18M7CDAEUAoaBGzwOvQf1AdVGj+Ar+HENsxHg1nr40QhDY1M4qyOEAajXe4TgMPQVXE9AK/cxEHzHCt+fOIawugpa34bgKvhFJ4MTPAZnEIzB0AW41iO0Ht4ZBC/PWxYtAAwdP3M3Ibj1gBBYKASSjVMBdoOAVY9QOfRLqZ8zpO4wCHvaTzmn4j2AFrBTAq11oONrCFMLP2/hewL1BLPBg6t9Z2E6YOg8BmsRYOAnGzAbE/i2RghcLP0mbM+Cc8CFlh2+m/KUx5YQNjgqFjzBVw6DMbHMbJDuZb4NMVLmRwaDMbwHe4LvLTwMhprrO7E6gR85TJdr9rCmAK33oNUphu2EobFseKuzJ8Z6mHj4aQs/BXzrgI5A0pCfrGEZBURug9bfGs8eth0Ifq7iEbTGQEd5og+o1zr49ZMY1k7AtxMMfYCZEkwbENZbVrYjB28rhGnFRkKblC0NQPCA6URObLSS33XsmUpkMFRA2BhAawMIFcLIwlsbjQXNCZuOWA41Fl676XlCmAaYlmA3PEfvagtPBh42etEeotxJU0NsAA3SMSoOew8ASTmP5oM9hGE+EOqug19bgZ8uYBgqoAPLaDG0BmNgpwF07DVQvQ2+ned7IMATNxMJUyAYbqx+Jtlx3so2hIAvf/nL+NjHPoYbbrgBAHDkyBE0TYPt27fPHLtnzx4cOXIkHpNvFv1cP3s93H///bj33nvjv//xj3/g+uuvx8H/+a84+Hq/cPz87qngDfDLC30BZ4m/nsfvZKnD1dVVbNu27S27nILTcTHIjuf+17++Vbdzbvh/F+ZrZ/DL/7N19vPbgUNnccwLAP79jQ85k+w4b2W7f/9+/OlPf8KvfvWr8z3FWWM0GmE0GsV/Ly4u4plnnsH111+Pl156qYT93gZo+O2d+ryJCKurq9i7d++FvpR3PIrsuLRQZAfjvJTtPffcg5/97Gf4xS9+gXe9613x51dccQW6rsOJEydmLNSXX34ZV1xxRTzmt7/97cz5lHGox5wJ1lpcddVVAIDl5eV35Au8WPFOft7Fo918FNlx6eKd/LzPRnacExuZiHDPPffgJz/5CR5//HG85z3vmfn8pptuQl3XeOyxx+LPnn32Wbz44ovYt28fAGDfvn344x//iKNHj8ZjHn30USwvL+P6668/l8spKCjYIiiyo+CSB50D7r77btq2bRs98cQTdPjw4fhnY2MjHvPFL36RrrnmGnr88cfpd7/7He3bt4/27dsXPx+GgW644Qa67bbb6A9/+AM98sgjtGvXLrr//vvP5VJoZWWFANDKyso5/V7B+aE874I3gyI7Ll2U5804J2WLWL00++d73/tePGYymdCXvvQl2rFjB83Pz9OnP/1pOnz48Mx5XnjhBbrjjjtobm6Odu7cSffddx/1fX9OFz6dTumBBx6g6XR6Tr9XcH4oz7vgzaDIjksX5Xkz3lSdbUFBQUFBQcGZUQaLFRQUFBQUbDKKsi0oKCgoKNhkFGVbUFBQUFCwySjKtqCgoKCgYJNRlG1BQUFBQcEmY8sq229/+9t497vfjfF4jFtuueW0zjIF545vfOMbMMbM/Lnuuuvi52czb7Sg4GJGkRubgyI7zowtqWx/9KMf4d5778UDDzyA3//+97jxxhtx++23z3SWKTg/fOADH8Dhw4fjn7x/7ZnmjRYUXMwocmNzUWTHGXChC33PBzfffDPt378//tt7T3v37qUHH3zwAl7V1scDDzxAN9544+t+duLECarrmh5++OH4s7/85S8EgA4cOPA2XWFBwfmjyI3NQ5EdZ8aW82y7rsPTTz89M/fSWotbb70VBw4cuIBX9s7Ac889h7179+K9730vPv/5z+PFF18EcOZ5owUFFzOK3Nh8FNnxxthyyvbVV1+F9/5151r+RzMtC84Ot9xyCx566CE88sgj+M53voODBw/i4x//OFZXV89q3mhBwcWKIjc2F0V2nBnnPc+24J2HO+64I/79Qx/6EG655RZce+21+PGPf4y5ubkLeGUFBQUXM4rsODO2nGe7c+dOOOdOY7Llcy8L3hps374d73vf+/D888/PzBvNUZ57wVZAkRtvL4rsOB1bTtk2TYObbrppZu5lCAGPPfZYnHtZ8NZgbW0Nf/vb33DllVee1bzRgoKLFUVuvL0osuN1cKEZWueDH/7whzQajeihhx6iZ555hr7whS/Q9u3b6ciRIxf60rY07rvvPnriiSfo4MGD9Otf/5puvfVW2rlzJx09epSIzjxvtKDgYkaRG5uHIjvOjC2pbImIvvWtb9E111xDTdPQzTffTE899dSFvqQtj7vuuouuvPJKapqGrrrqKrrrrrvo+eefj5+fzbzRgoKLGUVubA6K7DgzyjzbgoKCgoKCTcaWy9kWFBQUFBRsNRRlW1BQUFBQsMkoyragoKCgoGCTUZRtQUFBQUHBJqMo24KCgoKCgk1GUbYFBQUFBQWbjKJsCwoKCgoKNhlF2RYUFBQUFGwyirItKCgoKCjYZBRlW1BQUFBQsMkoyragoKCgoGCT8f8BeAUiXZb0eygAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "show_spectrogram(yes_waveform, no_waveform)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 梅尔频谱图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "def show_melspectrogram(waveform, sample_rate):\n",
    "    mel_spectrogram = torchaudio.transforms.MelSpectrogram(sample_rate)(waveform)\n",
    "    print(\"Shape of spectrogram: {}\".format(mel_spectrogram.size()))\n",
    "\n",
    "    plt.figure()\n",
    "    plt.imshow(mel_spectrogram.log2()[0, :, :].numpy(), cmap='viridis')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape of spectrogram: torch.Size([1, 128, 81])\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/envs/limingbo_sf/lib/python3.8/site-packages/torchaudio/functional/functional.py:576: UserWarning: At least one mel filterbank has all zero values. The value for `n_mels` (128) may be set too high. Or, the value for `n_freqs` (201) may be set too low.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "show_melspectrogram(yes_waveform, yes_sample_rate)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 梅尔倒频谱系数（Mel-frequency cepstral coefficients , MFCC）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "def show_mfcc(waveform, sample_rate):\n",
    "    mfcc_spectrogram = torchaudio.transforms.MFCC(sample_rate=sample_rate)(waveform)\n",
    "    print(\"Shape of spectrogram: {}\".format(mfcc_spectrogram.size()))\n",
    "\n",
    "    plt.figure()\n",
    "    fig1 = plt.gcf()\n",
    "    plt.imshow(mfcc_spectrogram.log2()[0, :, :].numpy(), cmap='viridis')\n",
    "\n",
    "    plt.figure()\n",
    "    plt.plot(mfcc_spectrogram.log2()[0, :, :].numpy())\n",
    "    plt.draw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape of spectrogram: torch.Size([1, 40, 81])\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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cWC7cM/tYQi7Qg5EqoicLZ3SsodQQqr0KtCwOzX9GbVlYWFhYvDqck0JkaVOAebU+8ppBTyoLgKqJeAi74UJS4wzFshT1o8dItLV9Eoejjmyun76+O474v1RWtLc3bPCfD+ydlv53bdnA/mg58aJzyuNEBqdaiMQGCJQ0nTp76eTvLykT7pl9LJ6ssHqmVpHB5CB/nS/EzojLhjEFMS4WFhYQjW4gEll3trth8XfKOSlEJEniptVNAGwZFRYM28R+MziRbXF0w2Qomj3q91XVy5w5XwKgt+8nZDI9k/+X00T9kQhe3n3+9KTvukpBsDldnQYhIixDTU7blLQX7Rf1PAzZRGlbPvn7S0oWkXYWkCoX53CmcSJDqSHigWoAtHyaePpvK3NGN00+treX7/aOnu2uWFhMksuNsH3HB9ix8x8pFMJnuzsWf4eck0IE4G0rGrEpEu0xsVxXdRFcKskOJCULUv6oAasT1FS/kYqKSzHNAu3tX8Y0TfL5PLpcCvAM1HLZnOpp6bvTI6wJQohMbcDqYK6AZJrU6FOzI266VFVV84DkCkz+fp7HSYUKecnJHgeYmGecOTOYHCTnrwKgKhbmrgN/GyXwJ9iZyHD/eIzv941hmlOUOv0qkl6/nvgjj1IcHj7bXbGYQoZH/oxpaphmkVj8xAUdLSxOlXNWiFR6HVy9oJa0JAZ8WRMCwlRFlVXJlnhFCu/hSJLEvLlfRpbtRKJrGR9/jNFh4WKQtCLXXrwEeZoyZ5zeCSFim3KLSDwc4h3bnqP3sYcwjDN3bRTGxwCQ/YdcPd3d3WCaXFzKntnFTDRn6IxdM7FomLEKIf6qYxF+FjYw/oYm9AMZEVOUNUwyx3ALTgnTdE2iv7+H4c9+lsQTT0xL+xavPqapMzL8x8mfT6aytIXFqXLOChGAd65uJiOLQVkqiiwXQxUTpqzG6T1BtU+3u5UZM8SmeB2d/8P2XdsBMItF3rlmmoqZAc5pcs3kdIMRZHzZNLHxMbZu3XpG7ZmmiRkR7hZ7hQge7e7u5q677uLOO+/kksBEwOpicv5etGAGs3h6E7BhGuTjGYbKyygqCophICdTPB6Kn9E5vJq0pw8FN4eK2tQfYOcf4PaL4en/nvq2gXxnJwCO2XOmpX2LV59w5EVy+UMWrrglRCymgXNaiFw6pwpvoJRma4hJ0VBtyKaMZIvRHznxCn1Gy0dwuWZQKIyTyNwDgIREjc85bf2etIgYUytEhvNFsnYn22fMA+Dpp58mnT59K0WikMCbEjEz3tp6isUijz76KAD19fVcWlkGQCfziFcNgQHFsdM73nhmHH/BQ9whM14uKuXWRMJ88+DI34xVpOMwIRIuTIMQ0fMwtgcGN09500Y+T6FPuAkdcywh8mozOPhbNm1+C/n82JS2OzwkxrTq6jcAkEztRdOsTSotppZzWoioisw7VjeRlUxMuQxKWRYOzS4sIsdI4T0cRXEwb+7/BaChZjseTwS/2zWd3T7MNaNOaS2RiYyZQbcPOZ8ll8vx9NOnv2fLcGp4MnXX2dTKiy++SCQSwefzceWVV9LmslOrFtEkGztFaMdpu2eGUkOUawGSqsR4hWisNhKkI5Pn0eDfhlWkPZlBShUhp0+LRaRYtYRd0TqSvXthCtxuh1M4eJCO6gCb5jbT23/2Y3NM0+Trj+/nf59oP6l4m0KhwJ///Gc2b556kfZq0D/wS5LJPYyOPjhlbebz44TCzwAws+1TOB0NmKZOIrFjyo5hYQHnuBABuGlVM2nJxLRVTlZXLcs6J2NEjJPYb6Wy8lJy6uVIksnsORtpqKmY1j5PuGayZknwTJFVZEKIzC6001wy6Gzbto3BwdOrUjqcGqa8JETitW2sXbsWgGuvvRan04kkSVxYih3Z5iwrVVg9PSEymBzEZ1ShyxJjk0JERPh/p3f0NW8VSWo6w8kC9vXjODYGGYmfeaXZl3Ogc4wnR+fwwlA1hLumtO18Vxcxj5OQy04+NfV9P1V6wxl+8vxBvv9MF3dvPPH7sXHrDr69tci3Htk1JbFRryaaliSbFdaoaGzTlLU7MvJnTFMnEFiF1zuXsrLzACtOxGLqOeeFSGuVB9WtYqp+pFJ11fKME8UWp6AZjCZOrijZXXvfiqap+P0hAmX7eeG3D1EYm1oz6QSTFhGz5FaaIiEykCtgMwt8pOZ2Wi5+hGXLRYrzY489dlqD80iknYqUiQk8kyhgGAZz585lwYIFk5+5olqUfd/DPIqu4GlnzgylhnAhXDLB8gkhEgLT5EA6x8PB2Gm1+2rRmc4hR/JIBkg5nXU7p7ZQHUA8OA7AaNYHw9umtO18RycZu0j5Lqutn9K2T4f20UNWwq88su+In4/GIxv2MWb62ZWvJBL520r7Tib3T/47FtuMaepn3KZpGgyVglQbG94NQKBstThG/G/TamTx2uWcFyIAtTUekFzImrAIlGVd2B1i4DpWhdXD2TUYY3OfRF/fMgCU8mepuO1zPPSZr0xLf49wzcAUWkTyLGI3drmIKXu46sp34nA4GB4eZtu2U5+4hkMHqEhCT1sbg9EYNpuNN73pTUjSoWyiSyrKAehhFpGyAYojqdNKXR1KDWGnDIB4QKQJtwSDUDrWd3rGXtNWkQOZHHLsUGXZre1TPxmmShNsrOik0Du1q9psRwdZu3ge/TW1U9r26dA5dkh45DWDf/79NnLFo0/QIyMjDISFFSePje6+kxOBuXQR4ySzm14KRfjMA7fzl5GprxGzfezQu6nrKZLJfWfcZiT6ErncAKrqo6bmWgDKAkKIxOM7MIypSe+3sIBXUYh84xvfQJIkPvWpT71ahzxpZjb7kCQFuSheLm/BBWoMgL7j1BKZ4Hcb+/FJeYaH5pNKlSHbiyTeqlOzaO609NfuFH6TXMEUmZhTJEQORhOsLqwHYN3wYjxeH6973esAEbiayZxYlB1OKNgLsoOdy4VAu+KKK0g53Xzj4AhPlrJZmpx2GpQUhqSwtaaAmdPRY/lT7vtgchBVFqJmxC9cYy2hEACKadKRyfHQeOyU2321aE/nkKOHzjscN9k9OLWxLfGuiewHiVDnziltO3awG1OSAIX2jVO7/9Hp0DEuhMWHL22jyuugYyzFVx45+gS9bds20uah9PK9PUffWftwgv1JfvHZF3nxj50n/Kxpmux++jb+d8fncT7+byd5BiemYBj8364hnh8+0kIRmwL3zESQal3dW1EUF+z6E579L6CqZRhGlmTqzMWOhcUEr4oQ2bx5Mz/5yU9YunTpiT98FvCXiYldKQUIujQXupQGqUDfcWqJACRzRR7aOUy5mQRkDu4Vk272IoOZa6Y+aNUwdH7/H2IwM00oGMqUFTUbzGZYYRMpyBuHF7FzMMZ5551HTU0N2Wz2lANXU+Pj7Fi+nILDQW1tLWvWrGFTPM1tfWPc1nfIbXWBV1z3raVqq6cTJzKYGkSSSt931gAQiAvXDKU4n+/0jqK/Rq0i+6JppJS4DrJfvJa/Wd87pcdIFQ+txoNDIzBFRev0VJpEVMTjSHKAquazv89PR8kVc+GsSr77LvFO3r2xn7/sOVJkFItFdu3aRZpDQqRj6MTVQ4c7Y2DC/pdGyGePH1j8UizFghERH3XRwGOYiTMv+NaTyXP9tk5uHwjSykEAAnFxP880TiRfCBEMPQlAY8N7YHAr3PdhpEc/S2tCuD9jMcs9YzF1TLsQSaVS3HzzzfzsZz+jvLx8ug93WrhLAZNKqYaFDSEgxC68x58UH9gxTKagM9slYkkSQT+OdaI42rj7uSnvqywr1M+ZP/nzVNUS0U2TgNRDmRQjV7DTHp3Ns+sPoCgKb3rTmwDYunUrQ0NDJ9/XmIe+tlYwTa6//noURWFHQgi7ZT735OcuqxSD2y5742kFrOb1POPpcZC9tKQNaikHSUHWCrRFEuiKjBPozORfs1aRA0MJJKAmG+EjOx4A4MGdw0TTZ7YR4OFkUoeu61jGB+NTs6otdHeRdLp4aeUV/Onam9gdOPF3ppOibnAwJCwic2t9XDqnmo9cLur6fO7PuxiKHdq6Yd++feTzeQqKZ/J3/ZE0un78OIt4vINZ1/0bLVd+iW2bPsvIyH1kMn1HdSv+9OAgSyI1jOe/jaEtIrbu9jM6v3tHI7x+Szs7k1mqFY1mxDvZMijOS8SJnH7A7cjIvZimht+/HK93HjSuhPM/DJi0bN1MdShvCRGLKWXahcitt97Km9/8Zq6++uoTfjafz5NIJI7482owKURKCxtZEhYS2Xb8omamaXL3BmGNmO0VA5dWNCh/QMb9uMJw+Vunpb+zz1sz+e+pEiIDiSQrJRE3kOouQzdVXgqJFVZra+ukNetkA1cT2QTlxnIA5sVCNDWJwNedSXE9l/sPCZEra2cB0CvNIOQLn/KeM8OpYbyGm5SqcmN/gS/3g7rsZgCu6BQr4KqCGKT/9wytIntCe2iPtJ/2949GUtOJBsV1WRTq4fpdL+BR8xQ0gz9smZqgVUPXKWQOuX4O5hsxB6cmYDXf1UXcW85gfSs9zc2k7NNTUfhk6QunKeomHrtCY5lYVPzr6+exrClAIqfx6Xt2oJViO7ZvFxbAgnRob6WEpjI+Pn7cY+SlP2Fzx3AERsjoD7Nv/7+xfsOVrF13Ibt230r/wJ0kErs4MBLi3U/2ky7cSsFcQFT7Z9zb7oL8qWcWpTWdT+7v49b9/aR0gzUBD/cvkJDQsRUM/JECOjY0LU4qdeCU2wcRpDo8/AfgUJAqkkT8ovcSW/UmJNNg8f4k8sEXzkjsWFgczrQKkXvuuYdt27bx9a9//aQ+//Wvf51AIDD5p7l5ejaNezkTQsSul8q8KyIbRRQ1yxwzeHL7QIwDo0nsqozTFBYRs6gjpyUSGxTak1Nbfn2CthWrJ/+dM2yQjULuzETb9o4OViFMutVbxIS1YyhFPCvEyOtf/3rsdjtDQ0OTg/fxeOqZJ1BkH85slgtVEcSomya7kkIQHG4RqXW6aZHFwL+xPnnKmTODyUEqiwGSNlgVFYIwmxTtLesXq8WwpFKmyHRm8jwwFj2l9ico6kW+tPZLvOuRd/FE79SVMe9M55BKgarzVCcScEOXMOXftb4P/SRSyE9EvONI8ZTO6jzzVx2toJNNJRk72EXHhrVsevDPPPXzH3Hv1/6TX37qI/zoH9/DA9/+H/a/+Cz5Y8QI5Ts6SbncrDH284n+37E4eeK4iemkfVRM8rNrfZOB0XZV5vvvWYHXobKpN8IPn+0iHA7T29sLSETyh4bClCkCtI+FrmfA8yIAw3vfQPjAG/B6liNJNgqFIMHgX+js/B82b3kbw3supWz2DwjN+jPJim1oZg3F7AWw43endE67kxmu2dLBH0ejyMBnW+v48/LZuAodAPjSGvvsDoKmcItFYxtPqf0JotENZLN9KIqX2to3l863wKYtN7PFvZn4ktchm7Bw1zC5jntP6xgWFi9n2oTIwMAA//Iv/8Ldd9+N03lyVUa/8IUvEI/HJ/8MDEx9CuPRcPmEEFE1MWEaqg1MkG0JUnmN8DHM478r1Se4bmk98VIFUkepIuZwhcQVzVdMS3/d/gB2l5jI06aIizhTq0h3/2YaGEYzFZo748y0x9ANk/XdIuDT5zsUuPrUU08dN3A1GAyye+seAFZu3Ya7qRUQlUOzhoFHkZntdhzxndUuIaQ2V6jo4RxG/uQLeg2lhqjQAhRkmJMUq7REVrQ3IzRMoGCQtdk4XxJt/m/vGNppTO537b+L7ng3AUeAC+ovOOXvH4t9qexkxsyKqkVkHE7etetJ/IrBUCzLMweOvzo/GYZ+9lMAZEkBWQKK7Osr5wf/ch//89n/w/e/8RV+84uf8shDD7D2pbXs6ejAnq3i+qqPkt8X4bEffofb/+lmHvj2V9j3MlGS7+wk5VC5NrmeL/X8hLbQ1AbCniodpYyZebXeI34/o9LD/7x1MQDff7qTPzwjtjBorPRQQJn8XNp0vMIFGS1qPBmK87XuYb7+2LeQ1RzZrJfuUDUDHZfhSH6Xyy/bwcqV99DW9Bn8udXIRQ+mUiBTsZ/wrEcYXv19QrPvI6m9C3P9T8E4cZqtaZr8bCDIm7d20p3NU++wce+K2Xy2rQ5Vlkgm9wLgS2p0um3sz4jn/3QDVoeGJ4JU34KiiDEmGOxDlvOAyd56jVhNFYoBjj9/AoZ3nNZxLCwOZ9qEyNatWxkfH2flypWoqoqqqjz//PN8//vfR1XVo/pgHQ4Hfr//iD+vBu6SEJGN0ipdVlBNFa9brKyOlsIbzxR5eKdYNd24oh695K5oNsV3wjVOllUvm7Y++6vE5m6x4tQUNTM04fMdSTRR1Zrhshpxzs93hCY/c/75508Grj7zzDNHbcc0TR555BFMA1zxYZoGB1FrRTrnhFtmideFIh1pvr84IM5jh1ecV3H05DN0BpODVGoBKvMmMjBgixGyi/uh6gNcPi4ESCQcoVxV6M7meWD81KwiI6kR7th5BwD/uvpfCTimLhBi02AMSTdRJZP5Nh/3X3ktDkPj9f3inpxp0Gq+s5PQOmFhGa6sZbRS1PnIE8ZuVuJz3sRfX/8Jfv7ez/DTWz7LHe/7P9z+gc9T1fomZElm9pzrKG9oQi8W6d6ykcd/+B1u//B7uf9b/82+F54h29FBMOCmsVRe3Fs544z6e6Z0jgshMrfW94r/e+uKRt6+shHDhB9vz5A3FeriR+6plDGdHBwY5HfDYT59oJ9LN+5nwdo9/OO2dg48/jALisIaNj4yDySJZKCdLet3oShOnINtOP+wivoXPsHM537Alv5vMLOjQHVQWBmjTc9RlMpIh+ZB+2PHPY9wQeP9u3v4j64hCqbJG6v8PH3ePC4sOySwQjFhnfSlNebXS8i6EOCnEydSKIQJBieCVN916Hp2dLPhD7ey/fefIJlup3fNpUQDKnIxB3e9DcZPzw1kYTHBtAmRq666it27d7Njx47JP6tXr+bmm29mx44dKIpy4kZeJRSbjMOtYsp+0MWk5dScOJ0TtURe6Sq4b/sgec1gXq2PrsExYQLWdcrjYjAOzFmIKqvT1ufy+kYAopnSLTwDIZKKhKnzCHN6YriWQGuGy9uECHyhIzjpmjo8cHXLli1HNV/v2LGDvr4+kAxm7t+KBNgmhUjJLXNYfMgEl9e0IZkGQ0o1Qbt5SnEiE+Xdm0qrwV2e3WyeIQZHLZlmVVjc033uMj5QLSanU7WKfHPzN8lqWVbWrOT6mdef9PdOht0DMQAaFAMFiWcvv4K4x8t1e59GwuTFzhDdwdOvVjr+3dvIK+I50e1uUn6RVbR3xjjhgIQvZ/L+Z5Nc0FPAIUuoEtRlDRbHxfWsTtr4wFd/wPu//UPWvOPdVDQ0oWsaB7du4qnvfZtEKk/MH6ApJ559qazlDK7G8UnmTpzpM1G8bHa156gLnv9+y2IafDZSho2NehtqTlicGhHiOI3C2HiYz+3r4fcjETozeWrjYd6z7TkWpjooKxvDNCG7/yZ6q5pAMhnUtrH19mcJ/3Y/RrqIXOvm4xf7ebEsT9togoZ9EMkFMO0pUrVbSWjvxFz3k2Oew45Ehqs2t/NkOIFDlvjanEbuXNxGhe3QmGIYGrmMeG99SY2438b6tAqSg2IxSjp9ai6ykdH7Mc0CPt8SfL5Fk7//xZYwzthzyMmn6epYQiy5jR2L/CT9LrHFxF1vhUjPKR3r1cY0TYpT4OK0mB6mTYj4fD4WL158xB+Px0NlZSWLFy+ersOeNi6fHUMtRy6VeXdqTjQ5BrzSImKa5qRb5t3nN/PABuGnlYt5fKMi9W/2ssumpZ+maTJ+x06UDjG5poqltMMzECIHdz1PvUsEdXridmQVLlg0C7siMxTL0hM6JMRaW1tZsmQJAI8++ugRgavpdJonSlvAF6r6qC9dN7VU4GoiY2aF75VCpCEwh1apF4CN9RmKwycfJzKUGqJSCzAzbRCWknQowwSrxKAjx4sstGfwaCYZm0p8dJQKm8LBbJ77TtIq8sLgCzzd/zSqpPKlNV86oiDbVDBUEl3z1QzDS3+M4kly9xvfQl0mwgVRkZp51/rTS9HObNtG6plnyJUmsEviTt7WJQqbXZR8kmuu/gqzVlajGHDNphS/GnTQd/FSXvQdKkomm5DviFLd0srF77yFf/jf2/nAt3/Imne8hwZfGaGyJrIBL+WaEACP/2H/KztyhsQyBa793ous/p+nyBaO7dLIazq94QwqOpv+8gd+9PNfoGlHuvm8DpW31UaQMTiolfOYIYK/Z6EwkTtjNwJcLhX45+ZqvpYP8vada3HlMsyYIcR3emwhUamaJxaspEKpBcngL6NrGZfj+K5o4tG3NbLVI3FdajcAm4wFrB26EIBg8/MYVJDqrRSpsS8jqen8454eRgtF5rgdPLZqLh9sqn7Fc5fJdCOho2gGpgSDtkpGNYWiXcTWnUqciGmarwxSBR7bPcLOQQMQ73lxgw8jmcZQZbYtcmFUzYHkCPzmLXBYWrJ+koXeXg2+cXCEhWv3cPfIidOyLc4OVmXVEm6/Hd1WOVnmPZB3kDPFgP1yi8jm3iid4ylcNgWHKlNIis/JhRxVpWJcq1bfMC39lCQJiinsknBlZPQJIXL6tUQG2/+ALJl0M5tWdYiQGSDsamV1q0i3fqEjeMTnDw9c3bFjx+Tvn3jiCbLZLLW1tQw491JWWsSrNTUUDIN96VcGqk4gyzZW2ESdi03V+iml8A4mB6kuVjAjbbJT7cOXrsJwNQBgy4VJZfdySVDc1z8WFD7UKNw/3+0dPaFVJKtl+drGrwHwvoXvY0751O4sm9R0chER6HyhIZGs24RXifDgZdeQ8jq4bp+o3XLv1kFSpxA3AyXR+v++A8DBOiFEfPYI/qJ47XMhJ2mlj/PeEWfNW2eCBPteHOaB724jtUNYCcYdYvJL7D3kopMkiaqWVi5+581c9YYbiHkrsXtFm0nJi79h6ku8B1w2oukCulZgS9+xq872hNLohslcV4KfzFvNj5sWsGnnriM+k0gkyAy1s1IVeyhNCJEaJCpLE65Xr+UftCzNLz1N/4Z1mKbJkiWLaGoWgj/ecwmmR+EL+wrckF5Ag15OUdJ5wrub1DIXdwyLSe/q6A4ADsgLKdtViZmV0Mr3U3CNkdRuxFj7ylTeL3UOMZQv0uK089iquSzyHr0e0WBIFB/0pnXifhtplwhiHzfLAIhFTz5OJBbbTCZzEEVxU1t7HQBDsSyfv3cXrclDAsPMx6j6dztlv1GQ+hWCb/xnKG8T489v3grpELpm8Lv/2sAzd+0nl35tVGCNavqka9jitcerKkSee+45brvttlfzkCeNy2fHVH2TG98FMk5MOQVS8RVFzX63UUz61y2t4xdre6hEzLiKXsRmmKT9NvyVddPWV3vsL9jlUnXVUpl38zSFiGmaFBwio2Ir5+EzUqzO384V39vEpXPEni0vdIaO+I7f7+eKK64AROBqNpvl4MGD7NwpghSvu+46UuksigmmLKNWVdKezpE3TAKqQqvLztG4oOTS3+b3URxNY56EKTWej5MsJmks1IiHWRbf0SWxoncVMgyEdV5XKvZpSCrt0RgVNoWebIE79w+z7a99x1zB/Xz3zxlKDVHrruWjyz56wv6cKhvH4shZscK/sFCHkgvgJ0bBbmfzZfNZEeykKRMmmde4f/vJ13ABSD37HNlt2yioMFQpnpNqxwvUu8XEXEjZ0PMyfX23s+qNrVx36zIcbpVYTwJ9SDzT354l0loL7VFM7ZXXKN/ZSdLlxuMsxeGYNcw+b8ErPnemSKbB13x/4te2b7K+49h7OE24ZRp9WdJONzG3j9s6+o5w0ezYsQPTNLlW3cFl8k700jDoS7VTXRTiRDHK2Lj+JQ4ePIjNZuMtb3kLl19RS6EwimT6KA4v58YivG2oiIrCnOwSbAUfuUKeO3/zG1LRKPUqNEfFOzEzKPHuJ/8EvxZVf0dan8OgjNQeIHro3X08GOMPoxEk4AcLWvCpx3Zhd4w9Veq3xrirmf0dlaLIWslFGY1tPOntEoZLQaq1tdejql50w+TT9+wgkdOwuw+lfRuSzrjbi3uDQvV3bEQ+/mMizv8P3d4AoXa46210beglEcrRvyeMzXn2XfDLSwufCYusxWsPyyJSwu23g+REKu03E8gLI60oanboAY6kCzy2R6zcW6u8dAfTlMuljfE08TmjeXo3/XJUm9gVIUQ0SUzqRrj3tNoaWv8MnkYx6WzhfGbmxWSnGyZrZopCY+u7w+S1I83hF1xwAdXV1WQyGZ544gkeffRRAM477zzqKr2YJYOGUlmOpCjsSE4UMnMd07VxUWUtiqkxavMzqJpo4exRP3c4gykxcVRqwnoTsYnVsi0/g5xNHGezspGLa+04dJOsKvFgPMc1lSLY9H97xlj7QDcHtwdf0XZPvIc799wJwOfP/zxu2ystOWfKM6WsJJffjhcZV3AGAUTA4ZaLFhOqkLmuS6SK/ual3pOeWExdJ/jd/wXgsdUSXjxUzIsRu7pI7opuXLI4l1zIQTS2gXh8GzMWV3Lj51czu0o8W2HNIBEsELZLyAWDfM8rS87nOjpJ2hVSeRf/mv8k78x9lvYdRw9kPiNifVwae5CLlb3M3/3NY36scyyFV8pjyocy3dZXNbF2l3CRGIYxmX6+il18p/mlyXyZLUaG1cNPYtfzhJBp0iuoqanhn/7pn1ixYgWjI6V01ezlzLA58Bkw4pR48No69MV1+KOL8TjK0LIZrtu1js8YfTiMLFHTS0upLknd7hRyBKINL2FKGintbRjrfgFAsFDks+3ieb61pYYLyo7M+nk56dKeMr6UxrqODzBrw1U0xeezORZElh0UixHSmRPvslwsxhgPPg4ccsv88JkuNvVGcKkSq917S58U79PuRQvIXiRh2EzoTzD23TvovMfG0OZa0jsPsOu+lwBYfHkTinL2p5hlfmFRak/nyLyGXEYWhzj7T8lrBLffhiTJ2EquGZ8ulueyLU4kXSBRCpK7d+sgBc1gYb1vMmumvJShQU4M1BXzpreUva21ErssXi7ZLgSTUkxOHv9U6HjhR8iKySh1FM1Kyo0kN2tFLjYlmnxOqrwOskWdrX1HxlMcHri6fft2wuEwXq+Xq666itGRzZSX3DL2OuEi2Zk4tltmgvqyxcxEDJxbKuSTcs8MJYfABEdpJ+J+lxBSZWiMuYQ4SSt7eCT1MGtC4t6qhskLo1G8BZOoR2Z3q53w0JHBoKZp8rWNX6NoFLmk8RKuarnqhH05HXb0xwBoKGVuOYYq8SHuY9RbxkOrDa7u34JTK9A5nmL9wZPzc8cfeph8ZxcZp8SDa2TKdQ+YoHsgXuWgzCwV8OoW96en98cAlNW4md8g7tFw0eRNnUX2OsUElNt/yCUSyxS4b9sgX3Ss4o7Gy3hiZBn3mmsYo4ynuqZh5Vkxk9SbfgTADbmHyGz89VE/1jGWZJYcIu04VDKgqNr41sFhDMOgr6+PaDSKgzwL6aD6Df/GhONjt38xA84GVse3MYrBXL2e8+dejRwoZ0tkjEeCMR7lBn6mvZ0fXOjhAxe4+felTtaWycw9vxbZtOEOLSbm8uDLZwmt304KF5v1+bi7RPC0Ypqoz7pxKXHiLVsx8JPaHMXMxvhs+wDhosZCj5N/azu+RTWajVBeek5cWZ1cQmQq1SZnMJYN4/GJOK6Tcc+MjN6PYRTweRfh8y1hS2+E7z0t4t7ePUfCpYv7KdvnAhJGKoLtYx9i7BtFYu/WsM1twywUSXQr7N66mvFMAzIF5i06+9YQgDq7jRq7igHsTZ14cWPx6mMJkRKTtURK+804J8u8i5e9PywKm/1+k/ARr5xRzoHRJF67hGmI77hTwixcPncR04naNh+nXDKXmhKZUv0TM3pq7hktGiXt6QZgG+fRVAhTNAJUDPyclb0/JhlNctmEe6Yj9Irvt7W1HRF4fO211+J0Ohke2zkpRNRakaGxc9Iicmwh4nbPYrEkAh031mgnJUQGU4NUF8tRTTFZ7vWKAdQlaYy5RCxIVQJ+V3iQNemYOI5mcNkLCdbsE4PSiwtdDA8euVHbX3v/yoaRDdhlO/9+/r9PeYDqBP0j4rgLbGLQdg248ZcmmLg9wHANJKoMruoXVW9/89KJ77GRzxP8wfcBuO9CCU95LUYqR2pUXPuET6VcFVa8wmAbmBAOP0syuRc9WaDYL/oUWC3cW4mUsIZ17R7nFy8e5N0/Xc+q/3mKz/xxJ+uq51CUbQTkNO9VnuJO2zf557dcPCXX5uWUr3o7v7K/BwDnX/8VBl5ZZrxjNMFsJUzaId7fmU7xXm8rr+OJ3fsmd5FewgHsMy8lVL2GDDAnJTJMXipfw/L4LqLFGI1GFR/OJ1i0bg/X7RzhNj7N76QP8GwgwMYaG3vLFHaXq+xIZGiaVy6sqmmZPTXnY7q9xHNwF28nrs3CzGVLmwKCfx1IOeifI0RCMv8mfr/hKf4aSmCXJH64cAYO+fhD84u992OTQTJMRvUynJpYODWmFgJQtIuS9icKWD08SLWh4V0kchr/cs8ODBPetqKRFmMU8gZFfwXFaj+SrRWA4D4fksdO5jKD+H8FaP3THym76UYGW65CVrPMftNn2fXk1ZNZiGcTSZImxx0rTuS1iSVESkxUV7WV/OByaRMs2SYmhd5wmvUHwxwMpXHbZLaXVrI3rxCTHYZOZbxU1GzmzOntbN1SPKVAu2IhR6IoXrJ4x6nt/xD6/W+xzxIv5hbOpyndR7w4DwBJUsm7HFw6d0KIvNJ1AXDNNddQXV3N8uXLWbhQDILDkU4qksKFYKupJacb7C8Fqi4/SuruBLKscp5LKJit5XYKJ5HCO5Qc4rz0YiRg0Flk2DGOIWlIEoyViXszI+gnp+R4np+h6DoJu0JFUmdZVxZbTifmVXjKOOQHTxVSfGvztwD40NIP0ew/VOE3GAySy+VO2K+TIVfUSZUCVS8oeRLUkES5IX5I4GeebuPXl2hc37MOgCf3jTIcO/6qLvr736MNjxD3qzy+SuI9bTdiaBqFhA0z50CSdZz14tok8zo140JoHOz8IYkn+8AEyaFQ0x5hWNF5PpPlFlLcmIzwlUf3s+FgRASE+hSuGevjQmMzv7H9lK/ZfsnFUgfVda+s3zFVDM/7AH/VVyMbRfjDLZA4tIldrqiTi43jk/NkSwX/rq8tZyUFTEnmG71j7N0rCu2tYC9c9Z/8ZesgslHk0rCosxKzl1OUVRqiG1CQeP2YuDYVUoI55gHe4I1wQ1eeL+7N8a6QeMajms7doxEqlglX5txhhXe89914yDBGDdKweLYKq9Yw6KnCntNwr5exy9swqocZcvr4D01YND7XVsfCYwSnHs6BfuEm8qY1evOHKi2XJYVbeEgX6fex2KbjuvPi8a2k053Isova2uv59/t3MxTL0lLh5svXL2BkZIRcwU2ucSYZv0m+pgUT2P3MUwT8l4hjxDeRa0rj+8yXCNaswlnej+zNkpupkeh77oTn8mqwzIoTeU1jCZESLv+ERURcEkMSVoYJi0jnWGoyZff8mZXsHU7gtMlcM0u4RuRCntqYcN/Y29qmt7P+Bpx+0Rdd18i7hRk3uv+lk27CyOfp3Hw3qtMgq7noYB5NmUESmtj3xZRdZAoGl84RE9a+kQTBZP4V7fj9fm699Vbe+ta3TloNhhP9VJQMDGpNDftSWTQTKm0qjQ7bK9o4nNXlZdjMAmGbk87oiQeNwdQgS9Mik2V7IAVImIhVWDRQBsCycAWqbqNb3c/ccVGwqaPZzlOOIrZ+IR7XNSlopTiYH+34EcFskBZfCx9c/MEjjvfggw/yne98h46OjhP27URs6IuACaZdZmVYHFvO9tKQnRAiAc5z17NttoRalWFpsAvdPFTR92joySThO0R9it9fbGBzebi6UqSS2xSTmqSIP9GbhQUmXgxRsUfc81D0CZJbegEw8zoPaVnu9hVY79ToxUABziv38J/XLeSFf3sd9zSNcUkmwQW+bhYgAmDtchY2ntmmbkclHYafXM7n9r2Nzxc/RI/cAqlRIUaKQsx1jaeYKQvLnVwpnts6h42vL5mDZJoc8Fcy5C2nlnEaFqyBxpXs2TNOfX4Uj5HDV0o/HrdXMzPdyUh+mFs6k9ze2ccPjP+P/yt9mdsXLOET7TneNljkU4EAammS/1zHIL9pEIuYBSNFWpKDvJ8/4zBzlA2JRYNj6wbiDjFe2J5zIRkmyTXtfHmJk7Rq43w5y8daak54KTJ77sNTLJV2T+kEIjfQV63S3mDDbthRDJUfbRlAkuwUCkEymWPX+JiwhtTWXsf9O+I8umsEVZb4/ntWkI6FKRQK5O1Vk5/P+9Pka1op5tKEfnko/qS948vseaEfwzCpnnloATE2+sIJz+fVYGIBZFlEXptYQqTERHVVpSREdFlFMiUcTjFwP3NgnL/uFUGq4wkxId98wQy0rBi85EIef05DstuxNTRMWz91PcPeff/KvjUvIpVun1k1F4Ds4N7jffUIEo88QmqOmIS7jWWYkkJTbpSU0QpATnGSKWhUeR0sahCrq7VdR7eKvJzhXOgw10ztSQWqTlDtX8hchD99k93AyBw//W8oNcTcnFhN7vSGuLLrZlxZUewt5RXBfmXZJGv63gJAtPBHlOIQ7c0KuWtryMz2YtNMxspUnuyNcCBygN8dEPuAfPGCL+JQDpWiHxsbY3BwEE3TqK8/84Dkp7rEpGmrcBLIy5iGjpzcR2tYuAmS+KixKaiyjZ9elJm0ivxuQ88rgocnCP/yl+ixGOFaF88tlXj7nLdDaYsCp02nLCGup1Y1iIKMbmokx5ZSFSqgFHxIhngPtNc18QubEHSzizLvwMnD+PihJ8AHL2mjxS8jdd3PDbN/wqf0h7BL4p2I11wDq/6/M742r8BdAekgqp5lqdzDB7KfxnCUwdAWePRfwTQ5MBShTRFxLEWveGbr7TaWVZVzeWkvqA0zF7GcvUhXfgnTNAmNpGjKiriiGj0GwD6fyPrZFnmGcsOOMyPcG9VVV5MdValQZfahc9Wz+ynvEg+6CayjwObZDmTNZPuTO6glzFK5nepgya1pmth1jaTNhTtYxLlL4pdagW0VKi7N5KtbN3DcqArDgGe/zkuPfZyZpbg0b0ojqtXS0Rwh49/FvrYoZek6xgtDdMfEexE7hnumWIwzNi6CzIuOd/BfD4nx4zPXzKXCTHD33XeDaaL5RKZPRZkQwMXKKgpVDQwPlN5lE5KJHnY9JZ7burmHJvtw8rUhRJb5hJWpK5MneYx3x+LsYQmREhOuGVl3gmmCJOHQHXg8YrLePRSnqJvMqvKwbySBXZX5yGUzCQVFNLxUzOMqathnzKB90zgPfHcbe188tXTLk0GWXWRzg5iKjuooVTytFMGxtuw4idCJ9yUxTZPwr+5EWiAmqF12YWJtzoZJFcSKLaY4SefFCzthFTlanMhRGmdESx9yzdTWTAqR47llJvD5lrAQYT7fXKEcdwM83dCJxsPUFoVJfKdvkLBnCEV3AAZOl8iMkZIZlkRW0Bybjy4V8YfuYKBM4dr0CC5VZdaIuA4/Gx7nKxu+gmEavKH1DVzUeNERx5vItpg3bx4+35m7H7b2iwDgugoRWBmLdfBsZTP7XhRBtqakEFNyXNt2LftbJJrLxqjKxIhkdR7bPfKK9orj40R+JYI4f3lxHklRuWXhLaSjYnJWcVAWF+JCrujGL4vJOkwVzc4b8AZXIiGj2Pv5TWKYdFGn2TPMW9I2FsQlvEgUB1PoT/0QbltCufIsZbYIWYRYy+o+3B+8G8qmYbNKSYLZYgfvG/376TdrWbfi2yDJsOO3sOmntLe3Y5MMTLuHSClmqK5kgftUUyWqrjEWqGTngrdC9VwOjCaRdYOmnHhP64riPAY9TWiSQio3xHCmi0ZJ3Ov6+neQ2R3GxGRH9Xr+efkdzE8+B6ZJlU0FJJ5Y6aa7zsZIjziuy9mCvVBgIlfDS45H20RhM+kZH3/QhUD+THueivHF6AeOYdXMJYT15/lvsKnSjbM0cjuTNXTVuGmNdtEUC1Kf2cOa0HnM0hX2hISLeHvXs0d1z4yOPYhh5HE4F/Dvj+TIFnUumlnOXK2XO++8k3Q6DYaGqdqQigUWLHyBcm8MgEJ1A8NNs9DG3IBJoXMVxaITNyHs/b+YPEbaNkA+f/wxKR6Ps27dupPaTPN0qbbbaHTYhFspaQWsvtawhEgJ1a5gdyqgeJF0sWp06A5QYkd8bmJF/+7zmqnxOxkfK5W1LmRRdQN7WxtjPQmG2mMkwlMTS/Dy48+b+1+AhOwS7efzwpwbsOXo3nLiaorptWuJ5buxBTSMosQmRfiYZ6Sd5HXRZr0yTjYjVnuXleJEXuwMYZyotkc6xLAMFYcVM5so7b78OIGqE3g8s1gsCbPzlkqJ/NCx40SC2SBz0i3IyCRVCKrjzFv0V1a+4ds0NHRQblMYq16JI53FV7OLK7rei1N3oRZ7ccfvZ1c4wZdaa1iQAEyTbfEn2RXchVt182+r/+2IYxWLxck6KStXrjzheZwI0zQ5OCysbfNK6YVSOkjY5iac9uA1xP8FfSbvX/h+AO64IMKbekURq1890/6KNkO3346ZzRKcWc7muRLXzLiGRm8j6ZgQPH41hzeloegmij1LoLYUWySbuPPVVISuBKDHv5W7tgrr143zHiAVSJI3YaC0Cs8+9wKkx8nl3TwXupSdlCqG6m3YnEevETMlzLkGgIsRAaf3x+fC678CgPbYv5PqEffHI0uM5YvIIxme+dNDom9bnmHZoHAl/KBsDQXd4IWOIKpRoCYvzrXRECt/TbKz3S/2idoZfQ7f2HL0VDVuxwWkR7YwcN7XWbXi5yyt3sfb5j2ClNWIlYLcDUnijxd72eGdTVovo9oU705RFeOGS8vzcNvF6IpKeVeOWX39nG/r5abYKCZOko8eZTIOd8PPr4b2RykqDprKqzFkCUwTSV3G87U6ZdnSe2IoOJFZHV5Kc064l7PpLXzhvl1HWNFM02R4SNQOeaT/H9g7nKDZVeQibSdr167FNE08Hg+KKr7jSI8hqya19XvxJITruVDdyPCeZVzyUoTUPrEh5jLvY+QmXvPS4YKhp457W3t6enjyySdZv379cT93JhjpNKtL1fEt98xrD0uIHIbLb8dQApPVVZ26k5QWg9KurS6bTFcwhU2R+Mjlwq8eDItBTC2kkQD7zDYipVV8Rb3nFceYCny+RTRWXIvqFG96KlaKxrfl6ToJIRK5805iq8Stz0RqCBpi9VaerSGvC9Gw1NaDVCrZvGpGOW67QiiVZ/9o4rht66F2oqaMt6TB8lXVdKbFD8fLmJlAkhSW+Zw4zSxxm8reYPKYnx1MDrIkI+JDBtwysh7HAGTZQLXl0ZUs+xZ8gFj5fDxmP55igMt7bgTAnXiYbn+e1bExPji7lllDETwx4S+/dfmt1HpqjzjWgQMHyGaz+P1+Zs+efcLzOBE9oTT5nI4pw0rECOlIRQAT3ZSpyYjnKlrpZbZcy0UNF9FdB8vLh1B1jZ3BHDtLe9QAFPr6iP3pzwDcfmEaJIkPLPoAAOmISPkd8SWJyjL+knvGVi+e61ghSOilMexBYcr/sVRFERtr5L3cII2z2COquw6XvGQ59Wq0y7/OE3s+yObEbObpwpVWUMrP+LocD7PtMtK6m3Q4yeXJl0i9cC/3Ph/k5/1XcFvXZThKaabpg7sgVsC2O8qP2l08vPkge7oGWTbQhauQI2x38f29nWzaP46SHULGRJID1JQsO0UUtpStIK/YSRYj9MY6UA5ew5aXPsnQ/C+SLe+goNvQDIVad4jGVC8aMMfl4OoKH5oq8ftL/fzZ8V7KxmOizdIk6CrkibgCbFslrG3vefpBPlD4Kq7XC+tdKjQfve+w+KPOp+CnrxPFwnz17Fj+LRp9Qli6Mzp/mTefIf+hidWdbqaQbSAv58lE/RiGTIUzTvu+Z3n3T9YzlhDvYiKxk1S6nb3hJdyzw8kCZYzXy7sJjY/hcrm48cYbKRQK6KawELsLwi3t9QdxZ5qpTZY2BLXN5qn8tYS0WShSHuf8taTdQlg7totxJRQ8vhCZN28esiwzPj5OKHQSVtdTZOQ//4v2Vat58zN/ASwh8lrEEiKH4faL/WYmqqt6DRFj4HYJYeEspVi+Y2UTjWUudF0nkxEvti8r/na0tREdnV4hAjBrwX+h2sQKdTwtUjudikbwwDbymWO7M3IHDpB+aT3aYiFiig5R3jqgJZH0OeRLg/keeRajNhFr4VCVyeJmJ3LPBMd24ksJYSS5XOw1ZQyg3mGj9gSBqhOU+xcyD5HG+1Lu2GbUwdQgS0tCpNMrIxsJSpmm2Gw5dDWLISvsXvRhMsEqbJ5x2oKrOc+8GAmTZP4unt+7g6oGL/7oH5GNFLqthWtnv/MVx5pI+1yzoBE5nxDuuzNgoi6L6bczM1ya4RMjuEsFoOrjwpwdcwco9PdNiopfr+znsmGx8r/zsUOr5+D3vgeaxviyZva0GKyuXc2iKpFGngoK10OlkmHQplKWKLlnaoTLJlYYx8gtARPaPWOsC4oaFJ9X76FtbwdXFh/BxCQbFxc3py0koy8k7puJ3VegXBlFNxVclYeCGqcarVDg3u98mzs6VvHH/qUsDe1kXmg7vTu2Ek/rFAJVIEno2RzlK9dg+m3I5Qq6rPLJe/exu1hHrR7m7ZoQ0rePJ0gMpmicKF9ua8LfEsInifdYk+101ArBuTvxNPqcP1G0PQumRHHwQv597ZfYFxYZZqtMka328Rk1/HxxG/PicYo2if86/0aSW8VeMlLpeXEUi9jdOj+76o0AXLJtCxWRCOHq3djdw4CDxAPrxfO19rtw942Qj0PT+WSveATbYAdGKRh7s2HntpBJIH9ocZBzD+NNtPJ449OUL6wlnRZu1WuqN9Myto4Pfe8BtvRGGBy6i0Tey+/2vptrbB1cYOvH0HVmz57Nxz/+cWpra9GN0l5RqRj+fJra8TxOdxLUDP7cApwhEYS7WZ1Hxj1I3eIo3b6ZGIro38CQsORFIuvQtGMvKFwuF22lAP99+/ad+sNxApSyMgAaUyLxwBIirz0sIXIYbt/EfjNiYqgrmWobqkpbeGeKKLLEx64Q1pBEIgFIYBhUlNLCzNomsknx/bLaqa/EOYHNUUUZpQqYtu3kfWIS8MoZerZvOeb3Inf+Cq3cRK0vYhpQqH8zAE3ZMfLG/Ekh8iwryRy2t8lEPZEXO48fsDoS3DfplrHV1LArNVHI7MQpiRP4fUtYhKiEudFmHLW0OMBobJg5WbGK3xuQkfUEaUOIIJstB5KJmunCUOzEC5chV4sN5K4YfQOyVImij3Nv9gm62ctgQPjmExUf4PejRxaGi0Qi9PSIzIMLOr4B35wBvS+e9PkcjQ09QgQYZXZmDIprrieG8DjFPa2PCpdfQvKTGtzNhfUXMq98HgfLClxcJibPxw4miaQLZPfsJfHY4yBJ/OiCGAD/sOgfJo+VCYu25tgyDKoOyuLi+VSrxESS1ZOYLjER3EEKE5lVtTtZePGVIMlILTUEyzWSBkQVQDNJ7xoh6WlkjkccL6LNwFE744yuyfF47jc/p2/XdiQJArYslT6d7f6leK98Nzf9x1dRW0XA9m5lBvPqgqDIVMwosDC5HxOJl7Q2+ryL+D8XrqYskyKt2Cg0qdgL4hpEAjL2aola6ZDw7a2cgaMsT7FoMLYrgBqaz4wN/8XzOz9AzNQ4IImaLitdQhBe5HbhVGT+a8/3aQ4WCSQiSGNjaBK4Dks4q6kv0tnSxq65C1EME8/zCsMjf8T3OuFiTY80oz11Ozz1ZcCElR8ge9FvGb6/j0eqnqC9IBZEHZpCsuIiqksTrFooYigF7K5xSM8m1hhjwQIRg1JeHqJczrJKP8Bdv/wZf3guzf073sXrzE4alASqqvLmN7+Zm2++GZ/PR39/P2YpzsYWDdKkJljQnsKmGahle4jorezN12IPljYB9B9kOGQwtkPUedGyfiL5C1DGZEw0QsFnj3t/J1L/9++f+g0TTXkm7iu+SGVaLKZ6soVJV5rFawNLiByGyy/2m5nYgbeiICwi5YeZPt+yrIEZlcLS0TvSC4hdd70lIZJ2isHEV+nE5pjeyoKVHvFiaZpOV6sQCgFb7pjumeLYGPFHHyWxQvycGXeTrRcZAlcH+zDxkjeEilga30MqFpv87mVzxcpqS2+UTOHYL/FQvGcyUFWtrZ3M2z8Zt8wEPv9iFpaEyLZyhez40Vcwen8WFQUTk16PjGzEJ4WIyya+k01vJRDvBslOblD4/ZN9Pl5nfhgTiYi6iy/v/iIANemL0Bxz+cVgkMJhuwpPBNHNmjkTOVXa58R3ZplRm0obt/mqnPizBqapY6aDeP3CvVEZExaRBAFikU1Ih7laHlmylzmxQQqSwl1/Xkvwf0Up9/ClC9lfmaUt0MalTZdOHitVihFxenWSciP+pIZpgs0Txed3YpMdyDYPu9HYnK5GwuBtsx9mYE4DfGkcxwdfJNEk2ugvicLsqIoh5VlgEwKtaNhxNExP/Zz9a59j55OPARBZfCUfmr2FW5q3sKVyNVtd88FfTiaTpmjKeEgwOi4EZ1k+yZWh57hQE8HP94Xq+egdT3JRX2lvpdl+Ek4hPAy/Su9AJxXSoZikSKGChgvEfQjtrKFm40dxJlvZg47q3c/e0i7AM709+LUIt607yHgszeriOj638QUu3SlW9z0NTciIzBqA6kwMh2bS9TbhJvSsVSjER0gvkHA4uwEbyY0lq+aajxOb8wV++ehP+ODML/KHTJ4am2hpvrKEuLuSmoS4N629vQBkPP2URZfQFeuiqkoUl2tsTHPBheehSxLlchZ5vI6Z+QIOSaeiuo6PfvSjnHfeeZMxcHv37sY0VBQzi5JO4LYVUEyThtEc9vKdyEgk3XOxh4axh0Tg9LjZRdYlhEkhXQVIyAeEy2lo88+Oe4/nz5+PJEmMjIwQiRx7U8PTIZYwUMpmUIxlmFGKYdplBay+prCEyGGI/WYck/vNuAtideouFdmSJPj46w7FB2zpEZYHuZDDVdRQqquIJsQlnU63zASuKuE60XMKo2UhEl4Vvy1P746t6Nor016jv/0taBq5C8V5menZjJZcGTcNicF7Qoh4tBQZ6VDqaluVh6ZyFwXdYMNxyoyPpEdOO1B1Ao97JjPlcTxmkrQqsX0wetTP+UeFq0dCImHLI5lFUroYSB0lIRLz+Vi6+3ZshSCS5kKSi2DKLBj3kPVdC0Bci+PSPbzhwJupkmTGChoPlXz7uq5PCpHVS+chFcUEEYyfftZMLFNgICT6N6e89JwURXyIr0rUhPEmxSo3QYCEKSa0N7a9kRp3DV2uGK/zC5/93TtGSby0HlSVH64WA/j7F74fWTr0aqdTJWudV8JvW4qqmyjpUvpng0SjezZIcHvp3l+/WKLeM87g4G/QzByK4mD1RXWYQKr0PcWsQDXGaFFFPINfHcPdPOu0r8mxCA8O8ORPfwjA5pkX8auqlfQHFqKaBdbI+9hwMMz20g7QfUY5Tc2tvGQXSlvJFpGAJdluLlD7AJNtCS+9PRXURkNoisLaC95AxFaGTVUoK0uyavbzk8dOFPyoDQVs7nIM02BvdC1p3aRPMZDtIeK6TH9BRpZMVmY38UBnkBdefAa/lGWe7SWuWy8E0MHGVgBiDi93z3s99aEgdT1paq68koGaOuQsuNfLDA/fg/8Sf+merSZp1vKLdIEbXrqRO2r+RERJU6/qVKpCiPSU34JdKxLIiWdywb59SIaCoRSYlaugO9ZNwL8CSVIpFEbweb/JxRfcQ96foWDKGCaUz1rGrR/9MFVVR7rVhofFeODOj4rYN7s4ZtNwDne5cPVdWaxGVpuwB4dwlOLUwkaRkeE55LNCgBQOCitZXNlHrvfY+954PB5aW8V1mmqriD5ReTo+xjKrnshrEkuIHIbLZ0eSJOylFb9SijDzesWL/vYVTcyuObQRVfewKI8uFfK4C0UcbTOJlgJVy18FIeKsLRVOi9eABO2zPVR4DfKZNIP7jqwpYqTTRP/wRwyXiVkvJpyqqqsYzBV4ffglynNiAsyVqnqG7JWktUNxEJIknTiN19AZLsQnLSKZhgYOZoVNeukpCBFJUgj4FrIAcQ5ro0fPnGkMV0z+OyELH3Sh5K5SVXEeBa8Tm5alvv936EoGsxSYmx7OUqO8Fc3WAsC12jvxFLy8WRMrpp8MBDFNk87OTlKpFG63m1mVpY3iDA+S4/TdbhNVeQ23wnxJWM2MjFh566WUY0dGCLgEAbIu8X822cb7FrwPgF2LtuIvpBl3BNhUt5D4m9aw1xGkwlnB9bOunzxWIZdlwgqtB/zI1SJwcCJg1Vmbock9j/Vo7JJlVMXg89e9Drd7NpqWZHDwLgCuXnAR/dUqYc0kL+koip157jEUSSOhVeNVoiiVU+uaKeZyPPzdr1PM52hauJR1V70RbV4Zz6oiy+sN9l2kcwV27xYTfpdeRf9QiHaHsMz48+JdrNOG+ceaA3x2TTkKcFCxo25NQdFg75yldNfNo6x5hCVLH2Rhw64j+tATmkWiRli/+tJ7ac8Ok5BNFIdwUe7Nivu3UtpC0SkzvOPJ0nXVqIqKiTdcLkRr1F9g77wR5vT2kBxMsSLg4c9Xiv2aPM8qhILPwIXn47DtZa+rjze1BLgt9QRRNUG57uXGsjyfrRUxLPacyb3mDKqSMXG8TI6szUHMX0PE7UOqNBg3FnHXcIhnbe/hfm7kF/mr+Y3rkwy+7hY2v+FGdl71Dj763htQlCMtt8PDw+RyMpJkoISFIC7qTgoouPIGrfIohh5HMZwo9kVIgC2yjYgk3q2urjUMJcQ5Z6JzkJMSpgt6fvLZ41Z5nXDPTHmcSFH0q5iMs7xUtXaHJUReU1hC5DAmy7wXhZnANMTlsdkTPPWZy/jmO5ZMfjav50lExUsqF/K4Chr2tsMzZqYvPmQCZ50I1JTj1ci6g4TfhkPEz9G1ZcMRn43dex9GIoF2eQWSbJKN2GlbdDVj6RRf6foBBWMhuqmhlVKXR5x1R8SIAFw+Ue79WHEisX5GFHmymFlHo5iYmp12Ku3qKZ2bz7+YRaV6Ihu0V1Z0zWbStKUbJ3/OyKWKoaU9NySbBphITnFcfzJErGI3WskU78jWckFfgljtv1Np/yRLtVUAXDii45IldqeyrI+lJ4NUly9fTuSAmFjyNheVjcffGfV4TASqGmUO2hLiWTPiYpV5d4f4P3myuqqfoveQGfnGuTfitXnZSw9XusV9uGvRtfxoqTj/98x/zxFF2CZqiNgknWfdMv8vI4RaQ0xcU2dtmBp3Kz9B/Fzl2kiFV6F1xkcB6B+4E13PUOu0c7BJ1GEYKLlnWpziOGmjEh2FYcmgL3Fq+x0dC9M0eernPyI82I+nrJzZ//gJiooMRYPnR6oxgUXKMFfb2tGKBdKmjVHDJ3bCLhcCdX5RrOoDxQhXR+5m/qjCjSk7dhPCug3vSyOYeZPdqy8gLC/DVvSSDdURkA/bbTtbheF00+IRk+RI4nkwTVSHsAruKQmRxa49qC6dBQXhUnQ3rsSTFlarZVnxHoUqGwm1tjJ7uI9MQafFZuPZCy8j4faghiQcOw1Ggg8ROF/i11UPIGd06vKVfDD9Di4IxLjEp5PPiYk8oteSM6EtKO7vvauv4MZv3cHvV13AH8+7ikdWXUii4WN8oTvKz4pv5c/Se3hcuoFnjAt5MmawO19go67zZPiVQaTPPCWySyqr+tFLBQVT25vZnzsfgNmxCKa+HwMTxT4PXbEh5XXanQ/jrhXWjEi4hZxrlIyrEede8Q7G7HuJ33f/Me/5/PnzARgaGiJ2mFv4TCgUCjgMIT66qy9iWWmhZVlEXltYQuQw3JNl3sVAq5ni8oylx5hd40M9bEvrTSObcOeF2LAV89h0A8fMtlfFIpLZsoXMli2oRTEoFTWNiu4bABhvSSPbdbq3bpxcfZi6TuQ3vwEgfUXJ9DtUQd2sObz+wC9pyhbRqSFvHHo5h5wNpF8WC3LhrCoUWeJgMM3g0cqvh7sZVtVJi8j+CmFBORW3zAR+35LJOJHthQI5/chqiKOdfdhQSSppNKCAGFBtlKwkMihKEcUu7pk/ncZQ8nTO7hTuGaC1U0c23RysXkXT8iYAtOEsN9WJNn7UM0xnp6gWuWLFCqIHnyOp3UBa/yeCY6e/1f2WUnyIWWanNSgEgB7uZVerRP/CvwJg5MUzmCCA6TDJxsQE77V7uXGuiC2ILttNGUV6fHWs674cO37eNe9dRxwrPSaqYXpsBZ7S84wrCnlJoqJkEbGXhXhKydGNgdeE64ee5JGDj1Bbez1OZzPFYoR9+z+PpiWxzy/HBKK5UhyOLKxJDilF3l7Ldzd8n+vuv44fbP7BaV+bCXY/8wT7XnwWSZJ58798jn2yeDebc3miUg0/5B+4T7+aekWo3k69GpD44j9/EMqFYNaNkiXCKOP5+Idp35FhhqFyaaUfp2mi5cCxMUjEW07c3UDNF2Saf+ekgkPCL2M6qDfKWVpxObKkkMoPMD/bhakI4TdUkIhqEg65yHnufVwgl1KZM6K/KXcdrhExEYfLW0gFmihPi+++1BFidmU5D18qCrV5nlEYGv4jiYuvxDEQ5oa1DdyydR4P2P/CGl/JglXajHO9U2S7zRwXz5InW3ofTRNnQcOfTVGRjNJY3MX55ktcYT7JW5Sn+UJbPV+f28SbK8W1eSgYO+K65/N5DvaIZ63KHgNN3Ov2eR/ipfgnSesBKmNFqvzrkJHQZJ2uRrEgmzvkom3mNuobDiAhkfR3EgtU4NwmxoPcUoPRb30T7Rgpuj6fj5YW8UxNlXtmbHAER8lNOeKfhb1UH2cwVyR0nFg3i1cXS4gcxqEdeCf2m5FRDIXRzOgrPvvcwHO4dTHBunM5JEBqaCEdF4q7vG76hMjYt75N3y3vI/hZUXQrr6Wp6HsDroxC0WbSsDpMMhRk4PFHKQwOkXj8LxQHB5ErA2S9YpBx285Diw/wD713UTBEwKpWdihAc8xZO1lZdYKAy8by5jLg6O4ZM9TBiKpM7jOz1ymsBi/PmHl6/xiFY2TCTODzLaaRQbwjIdgY5Nbfbyd1mIUm1SmOH3ekSdglZF0Mhi0NzciSOJ7NlkMuGWKcWh5boYAtnsG+RNTFsBWdvPfFJEVJ4k+JHQBERtJ8uElMZM/E00SdblpaWsjnn8Su/omkdhNG7iJcidOLhyjqBjsHRF+Ncjstg2LS00I9zB42STnEdSkWZRStSIJS9dOeJyfbuHnBzaiSyrbMOr7y/hnY1AJGdga28X/GWaqWOnmdBoSZW3NpDBQlTEliSFVwFEySBdBNmZ8jntl36BpXjTVw1767QJKZPftzgMz4+KNs3HQdC2vS9FerjBdNDNPEoJG0PpNydZAeXeXJIdFHf/LIPpwq470HeebOOwC4+N3vo3nhEraPh3nDng28afsTLLONEqYclcJkGnW3Xkmd30ljdTmjBXE+2YJ4n5MFJ/uy1yChc+X1djak0rw/M0xAiyPldOwbQ7xQ9KBnc5R1H6SxeCgGKmm4aTWr8Kh+ZvqFS+iKyCYkAxwFlaqYc9IqssZ8Hr+UIWm62LxBBIzHKlqRsuIeR/xleFMH8KVTqKbG/7l3F41pg/uvuAZdVXF0yegHBnm490+0jorxIxQb4vUb/LjSKkkdHKVA1e3KYlTNwFcQz9Jnfv9zbtj3CLIBn3kwws0bnuOd255nTfef+P5M+CfpZ7xT+zEfqdP5h4ZK5v5F1Mx5MhQnfZjIf/bxdRimhMsVpzUsXM+mLIPswjCdRPziXJeXH8DUEwz4+thVLkR867gbX1Fi1qzN1NV24YvPRVfrUTscyKYDoxzygRhjX/vaMe/9VLtngr1i7NZ1DQ3Y9lyMZbo4B8sq8trBEiKHMVnm3XCAIV5Op+4knA1T1A8Ff5qmyYaDG5BRwDTwxMVgkHGLIlieMgcO16m5Ik4FW309tpaWya3CC0YWyVRp7hCConJhGEdZnh3f/BrdV1/N8Gc/C4D6wQtBLlBMqzTNvhrt8c/jMgr0qWJTtJRdrNQkRSGruF9hEQG4rBQncrQ03mhoPzlJmnTN7C7tnHF4afe/7BnlH3+9hZt/vuGY+6UAuN1tqIqHyqQYSJ7eM8Ybb3uBl0r7s8gDYrLRnCYJm4RcqkRa6azA7hBCwmbLI8kmIY+Iu3BnMvgLeXbPNJFtwnLVOqZx/eY0XtsCJFmimNOpL8hcXeHDRGJ340zmzdtGe8d/4NB0HLKw0pjdpzeIHRhJki3qmKpEVcBBIG8i2WXMTAR3AUxtJUVFiBFfOkFa8qGhEIkcSheu89RxbZsItL2n9/9ha/opyDlGwz7+6a4t5IqHrmt8ULi3xg7TxYOqeDZzaYnnBy9mzLDh1bNcnhujinkMj3ezdmgttTVvYtXK3+N0NpHLDeIY+Rb7m+xoQFgX13/ceCOSBA957OiyTo1cw+tmv+60rg1APpPm4f/9OnqxSNuK1Zx/wzsA2J7TqUlGkUyTrK0MSUtyCVtAkhg1vCRNJ3NqvaR1nURJ5LqL4p019AKmmefKwI9o6Pky6YJGS66Pm4buo4w0UtEgdqDILy5+KwDnxbZN9iecraBVF8+T4V2OQ3ZhKyaY31/GG/rfyGXh+kkhMsd7ABPYbMzF3S7ceNo8NxTF+BDxl2ErdGEvFplpjpDXDJ574iDRgovta8Q2C55nZNbuegJvVsWUDNIODVfSTsd9bezo9lEsxT71MpNVHf0YiogZaRkeorwliKFIJNwmrrQQB57wYlpaPorPK2rKRKMb6d2xFWXrSwQSEbKGydMl90yxoLFjt9jPqK6qh2QpyFmzuZEkCcnQ6HCL938OEWRtN4lsM6OJd5FzecGUiLSXATBQ2YVaLBVpc9ThSwk3bW45JB57nOQzR0/nXbBAjGEDAwOl8ghnRnyolCZfjBOIdaFpcNWGJJimJUReQ1hC5DBsDgXVoSDL7slaIh7Tg4lJMHto4j0QOUC2lA0iF/K4cwUku514yRQ83fEhTd+7jdlP/JUFz4sIfx0D3dBwhS+lKpRHUqDp4lHGqwJINhGopZSVkV0uvh/v9TK7LI2783E0FJKItNZoTqTh2e0qC6Q+srlXZt5MlHtf2xVC04+0agxHOvBlwaZDzOtjsDQhTASqdo0n+dc/7gBgSWMZDvXY6c2SJOPzLeL6OU9QWF0FLoXBaJb3/nwjX7pvN/K4mExtNhsJlUmLSKWrErtNpMD6bOJ3QxUiELcmqSNJEoPx2QRaD5WTXtZbINObpaxGWFKiI2muV4UI62xoIpwXG3dJwZpJIZJvHztm34/HhFvGKLMzRy7dm3IVMMkpNt4x712kXeLYZXHhVkniI64dGXw8kcq7K7gLxTXIpat34rYrvNgZ4uN3b5u0OKVKrpnBUtZDwbmEAVupkmu4jYe73wDAedFNZAtjqJXzWNpr8pu9wpVXVraa8897mID/jbTRxf5mOyYwUhBtaCxFB56tEvfyoxd8dNK8fqqYpslf7/gesbERfFXVXHvrZ5BkmZSm05NIgSmCpl//lpt4Xp/HbkRMQY8uXGnzan2MlaxmDtMkkGyBUubX6ivtzPetxz++iTdIO0ln+nEZORryI3jdRSTd5L6qi3mqZRXnd+xhItl2LNaKy3SRp8hGTBaUi3TY1R0V1I9fxszYNXTlZXIGeBwZkl6VPUolbaV0NGn5XjDERB/xOcgrQlhf636Btio3mm5i2xHhl/PFYsC1TYYDwl0XrMjx0uXDuGsy6AWFmn0VIEHMLCMulXNBpwhidmaLuNwu3vvVp6kLjTNS5sKVaUA3FNyag3379lFWfgEAsdgmtjz6ABIwr1uI1IdLGWLPPbCNnK4jSTorzT30lmrLSAjLpibFGcnWkHYp2EyDec6nqSvmWF27ndbVwtIaPlBGPu/ioWyaMc8AAN9/WyNPR0XsU+5y0dbof/83euqVQeiBQICmJiGiDhw4cGoP0FFIj4sxIFdMsODAXSiygWcwx+quvCVEXkNYQuRluH02TNk7Wea9VhFWjrHMoYnnucHn8BbFCyUyZsRmd9ExsTp5NTJmAJxuz2Tef8HIUWQ+cw+mkVDxNWVgTpqGZ55kztoXmfXUE4QSYlWtxxrxbvgmAL+qexd1WRHAOBYVg4nfCPO44wu4i690vyxtKiPgspHMaewcjB3xf8PJoUlrSNciIW5muRz4VYVErsg/3bWVdEFnzcwKvvCm+Sc8P79vCRewnhZfitxFNcxfIETQbzf180Ezw7NyDK/hERYRXayeKpwV2OxiYgrYxOAXLhfCxJ8Wj7t7HAqtwuyMJCbs5i1xHB4xuUZG0ygHnqZJ76cgOXjWeD2J9e/AnlUOCZGQHbN4fPfS0Tg8UHVWKQY3KolVbsbm4p8vvRy5ZEGqCwqxlCBAQY1SLB4qtDavYh4XNRzalO8zl7yNX/7DeThtMs8cGOeff7+Nom6QKQX9pRw6DtVHuuymSYvIpqG3kyz6qHWNszC9j1hhHKW8lQu6bWwc3cju0d08/fTT/PjHd/LII9WM7luC4ozTX60yWhI6Tr2BlxxVjJhZXKqLweQgHdHDSpSfAtsff4jOjS8hKyrXf/rzuHzCxbMzmSGn2pAUBdM0abFnCJTXEaYClSJRXVgy59b6GMmLa+krFPGmZyDJYnFQO68MLvgIALca60lpUQwkumzNXC3th1rRxg9W3IgrqFFmCIvZWF6s6vvlEMOSRMg3H5+tAkXT0XJbSOUbcJp+9ueEEAtW2tFIo5iQDiioMwdwFsWzmXClSDuFxGnJhJhdq3PjqkYkE3pjMDCrBcmQmN8nBHFvTY7XlWeZfUM/0qw4nioxvqQjLlpGD+BAvPtl0ThGJo09pnP9lr8yXmZDNlWyOZHt8+TTTxIInAfA+NhahjrA5nkLi0fE+/RUOM5oMM2OXcIaUl3dy+xgmCBCUMqI8WyobJxCTGGwQYwXy8sOUCun+diyO6meE0S2GRQSdnqGSps42oUAc2t13Cun0E3QXDG+/gk7v507zrM/+iKa8Uqr61S5Z3RdRysFZeeMNO5ciCV+McZdvTNDz+Cxq73qZ1g52eLUsITIyxBl3gOTRc0qZVE0bDR9KE7k+YHn8Wji5ZSLeVyFIvaZM4mMCIX9atQQAZBkGYdXDLQFI42uB7Bny5ihigyQxgvH6Nq2DrWqipRxEN2MohdkVntUpEg3aWcVz5TdjIyE4jeJlkqBl9uzdBv19OT9r0i3U2SJS2aXsmcOjxMpZBgpxCYDVTvmicFkmd+NYZh85g87ORhMUx9w8sP3rsSmnPjR8/kWI2Pw3vyDoMrsn+HktvevpMFpYwST/zBkfhozCCkgTbhmXJXYShYRr00MNLmSRcaREpNUS2SMLYFW7P4hMGUGKhVkE8YHhIoaG34Un+/7vEkWG6Y9rb+JgcE34lHCqNIgslsCzaAwcOqm420Tpd3L7Mws7YS7M1jar8jvx++00dwoatX44t1gGiQJgATx+NYj2vrQkg8hSzLn1Z3H8urlrJlZyc/evxq7KvPXvWN85o87SafFMTIOHbd7JZptBiOqk6BRxQN5MdG8bc6jeKszxAqjSLLKRdHZSKbJM7+9neoffpbLg7/nBulp3mDEWZSMsL/JTtaAJDkkZPbahSCab6j0bPwhuzofPeXrMtxxgOd/+0sALn/fP1I/e96ha5bIgCRh1omJtbe3hyuqxLu2kC4ypT1i6sucjOZLQZ25BL1VG9CrxGSdDAcJLb+VmOlBy4qJPmivpiA7qM9GuMA5gOlUKEg2nmldzbxsLwB5FEJk6FWCBNGZq/6JpeWXA6DntmCYEovM1kn3zHClm+yAeI+MOTqSBP6seA4TjhC6AnkbGCEY036FXvVr/PO/iXfO1/jdikE0WULRRP8+Yw5wKUVkxWTj0jD+WcLKovQVuOnhP5F3CLFUFRrBLIjzXtWxi/GA6Is700jBlIlH47zwYAbTlNCMYVyVK1Dss2hI1lGe1MkaJt9/eB8ZNQbAPM8+xuXFaEHx7OTtEJUNilqKuv4C/RVeNEWi0pGl3tiAlimjpv96auvF4izZ6aHcUU7WXAzARR21XLtOYqRkMQ405LnvYplP1z3DZXdfzGef/ywPdD1AKCvGkwn3TF9fH6mjWE1OlnA4jNsQAnOk5Cpvye6hfl4ZNh0uWhtnpJSddjhPhRNcs6V9UtRaTD+WEHkZLp8d3VYx6Zrxm2JVNpYWFpHxzDh7w3snLSJyIVdK3W19VWuITPbXK/phGELpF4x5tKbrkYwy7D6N4VGxLXwwKAIJs4MuZqfXAnD/0k8xL1EqClZrRysF+VXYM6w3FmKYkD9KUOllR0vjjRwsZcyIH9ubWwFY7nPxw2e7eGr/GHZV5o5bVlHldXAy+P0iXXqR50lWRYrkTZNnpSJ311bzFkS/HywW+WkojlkqMFbprMRuExYRVykOpFg6npRNoOomNsOgJzmfwAyR4uyUTcYCCkbBQHVGkWr+F1UtsiK+m2ojxbi9kgPNCm45gSSBo0Xc3/zBI0vBn4jhWJbheE7sChCw0TouVmv7xoWJvbxGCKj5raIglzujYc/uIF4KWI3GNh3R3nl15/HgWx7kB1f+YNIydumcam6/eSU2ReLhncPc7XoTJpBzaOiua0GSSWcq+L72QbLADFeQVbU78NRlyelZcnoal3smq3ureN1fXsK2P0fg6SBLUnuZE3mG2T0HS+4Zk+GcuAcXSStY6ND4at8Bvj8e4rLcqQ3g2WSCR277JoauM3fNJax443VH/P9EzYe6Ga0AHDx4kOx4LwCzzIOkEEIzmi4wUhIiciHKX+b8nh5Xyb0VDvHCQJEfam9lMCM+P+hqwIHGeaM7ufTAfnzl4ll/rn4FS4cOFd9aqw4ypAzySdftLFPvx+Oro9rRBOjouc3MGK5nf07BMKHghYWDoh19jkYmEsCTF27ctF2MIUkXEDbpkXfyVP9TmFIU05TY3FRLZ60LU5bwSHnOJ8HyjjjxPPTRhrdKnFs87kfW8xQV8dxUhsPk54sFQH1xlFJxYSo1Gwc0YdE90NNOLtoMgLNiPXNW29DzO1kwIJ7BF51pTCTc7ihL4v10zngvaqm4a8Zh8nN/nvtsi/l4wyf4yNr/x6rsHVyav40fB5bznbX/yce6X88fKi/kucpL2ZK8innax4lMvHdKPe9+XuPSypsBuL62iSsSjXiyJkkjw197/8p/rPsPbnr4JkzTpLy8nIaGBkzTPCP3zODgIB5T9KG9XLxDenCc139gIUWbRHNY4/m/9BzxnfWxFB/a08PeVI47+o+/nYXF1GEJkZfhDjiEECkFp3oK4kGecM08PyjiMqpK23vLhbyoqto0g2REmE4rpjFj5uU4PWIC1k3xQhWMuSixYWY0fRoAR/1e4pF2xsdEbYCWWBpZz0PLhTxQcQnLo6UdfJ25yTY9tiIvGSK4LZ1/pel0orDZzoEY8VKdAcJdDKvKpGtmf7WIy9DHsnz3KWGq/5+3LmZZKevmZHC5ZqAoXpAKfGRA+JsfGAqjDqb5N1zMrn2IWiQSukGh50ZyozfglsuxlYSI3SYmAN0l7qGSiVCeF6tFZ0gm19ILGFQHDbrqVQxFQ8uVE9r7VsZGZ9Lo/Vf+v1nCOrFpnoiNMLGRPVCytHSfmhCZdMv4bKDKtAyJ/iWzIm7EWS6uTXnp2nlyKq7U0yQQ7oFYdBMvpzXQisd25PN21YJafvCeFSgS7HYv5tnKy2jy2Ig5hUUhG23iHmMpAFdX7USWTNz1YkKKFcZRquZyzf5K3HOKKA6dXNROz7MtpGtvoTpZRsolEyrXGS2lj5eFF/ORKoPeWR72ejxU1yw+6WtiGgaP//A7JMNByusbuOYjn5wUVRNsK20TsHKOuBejo6Pkcjlkh4tEacWrorGtP8ZYyTJQnjWpMCuI2cVznQyFeL4jyF366xkubVA56GzELRWoGxtg0Y7NfNBxD2Cyq3oWFfFDK/HdUoLL5PVcq25gSJHZ5Opkcbkooa8X2vF0echqCgfzMmgwa7gUjzPbYLxTxH7kbHbUohAOKReUJ4oscRh8cvnH+ZcLf0So+adI3hvZM0Pcy+pYBkxw5wxqOrNcHa/HVMVz90DTjaTs1Zj2UoowBZxzxDm5CgU+MvR46ZpIDBbq0E0ZzZbC0OoBqGzbwev/8RJUZTNz9t8LwMEaH0VZobZqgC0D72Og6CJbKl+gyQEcxqGN+wxTIW74GDBr6JYa6UBlBJOdsbns9i9ma2AVT+7xcSAl+pR1VqLLKt5R8Vwr+T6+9e4fc+fdZfzPbzRuya9kYeVCLqq/aPLeT1hFzsQ9s3v37kkhMljKiCwMdONzZQlfLsaw0FPDhIfFvd6RyPC+XQfJGSZXV/r50qwz28bB4uSxhMjLcPtsmGpg0iJiz5ZqiZSEyHMDz4EJjnxpcsvnsGs6eb94yV0+G07vye0yOxU4SxYR3RCbdxXMeRDrZ+a8m8kGK5BVk507P0E214NpwOJsGCQZ3vRtxrIFFpV2VB1JHpxs060U2akKa0Sm8MrMloYyF7NrvBgmrOsuuWfCXYyUaoiEAuUEHS7ktMaPHzmAacIta1p45+rmUzq3iYBVgNneTq4aLbIoriPpJhElTm15lN/gZUZZafv26EV85M4+9owLd5pqEytzvRSc6cpGqC8K4dYaGmWjZwneRrGT7cUH8sh6KUak/Y0M7r6RpZfewHsqy1B1k8EKFxsDS9GNSij55gsDiVOKEzkUH2KnWlEIFCGBiVHaPVXxiXvpqxSDpDerYs/tYrxUojqZ3IOun1yA3RsX1/Nfy7uRTIO9/kUkErcQLnV1IHcZRWRWoeC2iz556lKASawQRCmfSfNgiOraCG3XhLDPakFP5en/4fPMHRH7tGxr9RLTTdKmhqy7cEXmU6i10726lmTjyVdY3fTgn+nZsRXVZuf6T38Bh/vIQO+RvLByyMD5ddVHlCJftWIFT5kipbaeMOu6QpMWEW8hx1VlV5F2iec3Hhrnxc4Q3mKOtJYGZEac9bilPNKYQblrhGVz17G4QpxfZ1nT5MQbNFzohnjGvsrbOGDGqHY241K8QAG5mKEmVc+enIJtQMJWlNA9JpkKO6GYmFCjvgDuifvokvCms7yvDK4IVPPOmRcjyU7y9u2YpTohlZEc4aD49yWRNJ6kgSIZpPFwYLSFTJkQQlIhh7wyz0yzVEdnUKJu2V24ZolNHMt0O+0li9HAsBDhvsYckiRR3TyD6mA7ZckMuqLQX1WNLdlCT/I6IuvrsZcspF6zjE8mXPx67a956Jn/w7/M+CNfuehr/ML3NX5l+wafKjwMUpG3zXmAq3zPsSy+i6VaD0ubAmQlEySZrKsGOsKl99kgWtxK4xe/xNwhmP/nbdSYXhp9hwoUTsSJ9PT0kMmcelCpruv09/fjMUW8yoQQKUYTmN+aQ5vyGB31NiTd5Olf7Wd/IsN7d3WT0g0uKvPys0Wt2GTpeIewmEIsIfIy3H47kmRDKb2ElCoZjqXHyGpZNo5sxKk7wQBME08qjQQkbGKAfLXiQyZwlmJENFOYEQvGbMzoABLg4yZMA4qmEBm+qI5NN+G8D2HULsYblXAaYKoF+np3T7bpqmokXwr4TB3FIgKH0nhf6CiZL8Ndk66Z9hkzQTPw7IqQzGmsmlHOf1636LTOb8I9U2jr4dbOPKsjYmLZ6Rtljq0NDxItM01czT9HUmMMRnN84j43D3ZdW6quCoaioCkK/lySJr0SDANfPsv+7FIaLvg50vKn6a86Mt3aE53Nw7ft5sADPSzpFdaCnzbehE4Vap0b2WcHzSTff/JxIocLkTml0u4H0VlQ2rZGLgVn+qsOCRFM6E8NgwkmOvH4jpO/ePkHuCr0HACboq2oHQmkRIE+m8iG+DgZwoU8BQPsDh1HWYF4fhBJsVFFGZ5cDptHZ/uX34r/hutB15kv76K6EGZfsxMTk/GCGKw94yswTfCYCcKh4++0CiJDpmvzBtb94bcAXPWPH6N6RtsrPre9ZA2Z73HiVmTqKg+V9b9g9Up6PSIoepncTed4ioGMeG89+RzXz7oepRT4OzTcSyRd4LyiiPXSHDUUZRtzckOQkjGE0YlLm8QE/lzzShpS4tkOmx42sZyvFG/moFEO2QpiukmTR8SxmEaUxsj57Mkq2LtKInWWSWxkCbFSjZaI203KHgOERcSTTpPN+Ogfvhe/qjDLKVMV2oM3a0M2DSpTWca7fWwJCPH+dp+ofRMpVPGHe/+TJruwps3ODvCGQDd2jw5OAwwJ+wC0rPwV/pYNVOkyu/Ki5H0004RpgmaOkM8H8dc0IQFzgr0ADDZVUBmKkZU1HLqKOy8sBS5DbOTpzMewpzVGpdk0eEepmDnAFcouPuK5l5mVD3Bd2zPctPIBLk+8yOUDf+Gf5ktEZKF+05568p1dVFW9HoDx4BNsX+Tiv2+t5Es3w3ORTdxz4J7JMgmVlZXU1tZimibt7e0nfJ5ezu7du0EzcSEEiMMr7ousmRh5jeUH7+XR8zzkbBDsT/KHnz5GIp9nuc/Nb5a04TqJGDaLqcO62i/DVaolYi9t0FEsiBdpND3KhuEN5PU8rWorAFJR7DGjVlcTLW369GrGh8AhIVKQNSQymLjRcmWQizF7+fUE9xwauBuiWXRHGbzuiwQLGgtLngV7ZY5g/yGLiKt1JZ7SzsHH2mn30ok4kQ6xJ0sy3EFSkSlPmRxoacO2J0oxUaTG5+D2m1diV0/vUaupFumlEfk5GowYbxgRA9Xm6npaZJHml7CnUL1d1Cz4De85Xwzcjb5hdBvYTTERRH1+ZEz0ooSSFqtHe0ghqNbQOvc+7rrKy/euDxAJDGBIGiAx3ptk37oRLugQJubHqy5lv30xrnkVOGaJmetk40QyBY19I0K0GGV2WjOljcswWF0lnrkJi4i3UlxbxZBwFGWi6W4mEqljsc0nfe2ej8dYkGrn8rioAqv2pnBsDQESV6CySllHtTnOcFGsGj11GeJFsXuqWjWH1IiDoCLzp7HnaPjmN/F+5F+oC/SxNNlByiUz6JYm3TPO8RViczRHIy0tHz1mn9KxKJsfupdffeZjPPj//gfTNFh0xdUsft3rj/r5CSGySiry56/+Bz2bRGaHqqpUVVWRcIuA20vlXXjJ0J8R98pdyDKzZSZXLhL1VrREAkyDBbqwbEY9YvW9MlKqhNoozmN5zW58apqI009lTtzbuOEgi4uD+Sb8xiC1yRn0F0xaPCLzy9TDzAsvIKTJmJ3iOc/PMgkMXDm5iWTMrWCXRNBF0iWh6jrFoBczt4ViMUYrXbSMizGk0ZVAxUDqV/lxuI0xHOAuuZwGMwQKadJ2k0qi3Oh5AhWTcIWNaOk5MvYqSJJJ/fm/ZFnDRnI4iJgKmuYglxXWwlhsI5FRJ4ai0hoRaftdnlb+H5dyh6/IS2VpxGoLnLqIM3HkY5i6xAA16LpCtEYlodlxKQXeYRcZeQnZTWCWOOf0rnWEFHFd0+468h0dlFe+js1phc/tXc8nnvkEe/xxVB2u2GlwW/Ed2JRD1uTTzZ4xDIMXXngBtymuB6rE+eVuki4xNqdu+AMLl19Pzmnw2Crxu9ouPy+88CkeGP4x3qGNYJy8pdPizLGEyMtw+yaEiFh5FwwTTAhmgzzVLzYMW1ZahYk9Zoov22Pm1RYiYvLKO6qxy12lPgv3TP2cucQ7ZlJMK8i6SXWoAFf/X3CVMZgrTMaHFMtMjMOqK7rnXoKntDfMy6urTrCmrRK7KjMcz9EdTDMc7wWgKiWxtnIxylgOWZa4/ZaV1Pidp31+gcBK/P4VmGaR1NINtJQm8E01dQyXNjeb2PCuzO3h629fyp8/3Mbq2p0UbRIVkrBCjJfcHfFCGntJiLSGR/kxH6eq/n3McTtIuBW6m7IkyvaiqIfMstUJg1kjBUxJ4j+r/4FndoRIlp6TfHfspM5jx0AM3TCxu1VwqVSMlgIYfTYaSjVLJiwiqs2Gp0wErrryFRhGjp0ZIQxjsVfGiRyNvngfoxlxDy/U2rnuvJLZu2CiAP+EA5eyjqZCP4Yh9izy1mWJFdLopo5SNZfksJ+g/na6g530xHsYd1YRsI2yJCnK3h+olQlpJppp4C5UYEvMoJAfIhJ5/oi+6JpG15aNPPDt/+EnH/sAL9x9J5HhQVSHg6VXvZGrPnhs4TIRH7Ksuoro6DBZR6mmhaaRSCToS4jnYaE8wEXyXuKlCaRWVQgEAty06hYAFB1cti7k0l44fS7hSp0TET/nGkQ7qqxzYaOoihq3i2NlShsltjqSrGlPIkceZCS1hUpHY8k9o1EZ6UfN1uDqFs9NqsXBLG0+zqJ41uKuPHWlAn4Jnxh27Z0OHAWN8fG/YKY20Vhyxcz0R/C3iOfjA092cReXk/CKezm3a4Rs21xsyii3cB8OtUDCrbJnoZ9Cycrm3SOxNXU+kmyyatVdrKzZyQtGPZgmkYh4DwYOPk+sX0Irr6AinaQ8F6co2zlQ2YYp66QXifT2nM1AllQhMhECw6HlSacqMCWJdlnEfbw1kQDTZDxZT+98UXW4b8tL5G0TC4FKHqgb5J1/+RR3RxyMFCVcioMPLPwA9zg/wccfM/D+6B6M7KHy+hNCpLu7m+xhvz8R7e3tRCIRPBMbYAYcXFxTRtQv3q9NURnnVV9ijtfL3hY7qaowBiqbwh/EtvUuuPNauG0J7LznpI9pcWZYQuRluCb3mxE/m4AbNyYmT/Q+AUCzKlbdciGHuyg2u5vMmKmb/s3uDmfCIpJVAtglYcIsmPMg2ocsK7QtvYimtTprtkZJF2tQVr0fgIFkfFKIhJXDX3IT54IrT2gRcdkVzm8V1pYX9vYxomVQdJNO92xG42IA//A1s1k1o+Ko3z8VWlo+CECadiQgo0CvR+Z+by2aBGnEyrXMIY61rEUEmWmqPClEEmXiOsUzIQIld1ttIsJFxjpiY/fw+cwtfM/8CG+a+yuWnHcvtSv+zERRq/JZL/Ae+90A7JilEvU8iNwgJsjCQBLjKHE0L2cibZcy8Xy1jAp3z4qV9fz/7L13mJ1Xee79W2/ZvU7Z00cjaTTqxb3IsrGNDZhmSiBAIOQkIYDJOaSReg4nOek9J8kJISSEBELv3RUDbrKtYsnq0vQ+s3t96/fHWnvPyGp2AjjfOXquy5dtae/9tvWuda/7uZ/78UpygtfiK4304io9E0CKSh8py4WoUDyA5126KuXfDv1vwkqYm/K6WL+rC3tETsSvJ0C3XyUgjjFgFbCqstw70lPFB4rWMnp6PeX5GPHqT/Abo7/AV898FTEhAcZAVi6uZ/o1XHwW1Lti5F+FpoWxLKkbWp6e5Luf+Cj/cM9P8eU/+V+cfupxfM+jZ8NG7njX+3j3h/6VO971Pszg+YGqu8r98sqOFNte9Qa8UFjuVm2LfUdOkq1YCHyGxTRXBU/iCQG+z0hGskpdiR48VbqZiXwXyyqhCZ1TKpXak5V27sWEoY4Je/pkNdVkQjIBjtBxXPDNIE6yDd9doFD5Dg2vxoBiRRJL32LHWCfBmsAL+DDkMB4SpMtybBYjBU41ZJqxnFC9epZ8dj+Rxfzm7zA58zDdWXkf1sZy5K6tMpeCTAE2PVEhH1fNCqNlzNtu4S3Gp0lTpF7XObAjgWcJEmHVyHBR8PHKMIWxGxCax7t3fJQ16RlGvQ4KBXlNpbGvctPev8bt6EAAOxoHAPB7Arzvig9TVlobS/VqMgAjJN+HZK1IuSzfteM9KRxP0OdYJEoOC9VOvhh5M22b89zyU6/Dz/jsHfg6f/myL/Cxl+rM1eZJmSFembT4mx27+eVrfpmRH/9Z0m9/O2s+8XG08Eo7iM7OTjo7O/E8jxMnnp83je/7fO97kp1pClW1hIm772nqIXkP958ep+S4UtgsBP+6ZwOBmMGyM8TeyO9AIA7FKTCeX3Xf5fiPx2Ug8pxo2rzrntkSrPaacmGru3WiZrQlVG123TXWDFFckov5i5WaqRMhoMmX1fJGIC/LFjduWcPm0DKhmsf8xp8DZQufH5smbfvYwmNyaSUtEzJBi7YRUYxI+QKMCMCeDSo9c3SaGUMnmk/zB9dKoOP1RXj/Tf++fizPjc6OOwmF+glk5a7e9CDo1pg2Db7cZ1LzVzxEAAwjQXNot5myIqWWlACxUcuSFHHC9SrD65/kZdrX0b0KAb9IB0u0m4tEU7Mk1n6Ljq1fVffqOtbq++j3x7F0k8PbKjy075voiQC4Ptbz0Ik09SGVhNxdX1WWO/ebbxzALcmFXY+v9GhJKAYn5KzBR2PU0pmpanhenVLp8EWPZXs2Xx9/sAVEIuFeZh0Hry3I7wQsfp4gp81ZhPAZcBwO5kN4PoQSNkbEpmiNIYwAeqwPd/k0J2oBvn7662TYD0AsL9+Lxe4YU4bXMjfrXb6Gq3Z9leyJNj75Pz7AP//ie3jyK5+nks8RTiS56lWv451/9n946+/+GTtuf/k5wtTnxslqnbLrEdY0RiIhFG7GKOUILU6z95ispBpMCMLCYiQiUwxhu8Ea5c4JYCbkvYzoM5TCNu3BXpZFEM1zCeSU4VVMAu5nyhq90XmGU2fwhIbwPTyhs9eRKaByzxr0yJ0keraRtecYUDqR+ViYVzwl2ZXakI8WtPhOd4F0IQ9AMdmgUZcbmGqXPJ96xUTzYXxpiciCg+4J4kadeMjmH7vi/OGbdBqRIGsqZ9A0F831SbgOayt/SS8LVPwwR40kdkDDHBcU0nKe0huQyD3K6QM/RWH8WnTN4707Pk4pXiGXl0DE67JZGozhiAi6bmFm5XtCZ5Ci0Us0+wwAmpBjMqaDEZLjqaO0TKkq3zWnt8CxotSQ9M/UWay2U5+CYzf28yn3mxzs/iD7+u+lYdbpzvr8SvBVfPbOv+COhEMt/308z0FoGt2/+RsE1587X7zQ9Mzo6CgzMzMIIVpAJHdkH8E/+wt8lR6enZnlLQdPk1Ws95qOCLe/TYqK949tZu7H9sGPfQxGXv68jnk5/uNxGYg8J8ygjmFqCBFuuatm9Ezr73f37iafywMrZmZWqgffh2DEaAGZH1U0UzN1RyOgSUbE9gfxlqWpUt91L+eTU9fz0Pw6Mje+vvU9Malsp2MVZk6v1OpHIkovcAlGBODmETmhPj5tMarFyS69nYoZxkuYjFzTTfgiFu4vJDTNYGDgnUSyctI3fI83jcmF/cPDARrK3j2jgIgQGqaZAiChTJoaUbXTqmaJGUmGNjxDb99xfB/+kZ/j2fr/4L/zR/y5+98Ze+AVjD+4k8rCfvTgKXw3yMLD7+YnFqXB2bfsV3L/gTIzSQnWLqUT8Tz/LKFq0PJI2lAPaISTITwFRM7HiMSrDaywZCweKap26pfQiXxn4iEKjkPSUkAk3cFU3SKQa3CN1Y6G4ECHPGa34zLuPEO2JkFBtLtGyZbjSO8YoTz7DI/qDvqcS09ALgZPxOcQbhFf0zgeh3nbx/d9jCX49H/7n9z7of/NzPEjCE1j3VXX8ppf/k1+7u8+xkve/tO09z9/+/emPmRnPIxXbXBw3wEAzMIyZmGZw6elnmVDbweuHsIJSpAXbdRbNuEAVSOt/lzjyFCJeHQQD421xVmEK9BMj0pUAcOlCqmldm5SrIiuUj2n/Q5cX2AIDS/Rw81v+W80duygPdhHQI/j6hqdJQnQJlTR0FNpaCvKsZHoXovvyk1DE4zqFYcvbFjPVzri9Ku0zNpYDnyXNY5DLenxtfe9m7r6vcAc4EOcAhYGXy28ivJ61R9rVmNyYUXXsGlyjsUkzO79L5yY24Khubzrio/Sll2kUkkBMLtH/rsjM8bcfBsZbw5HmHxLfz3JogR5YVfOfYbmoYXk+Oso5pl1JKjqjNR4wJHsSNdiA6sSJrQwyTfmTvP1mUN42HSUB7nz+E/xex9v52WjSTJt12OaaRwnT6Hw1EXHQLOM99SpUzQajYt+FmixIaZptipmatUlnhrqwnBUQ9J8jqeKVcKqKuZUtcHaXR2MXNeF78MDHz+Ds+HVYIbPf5DL8QOPy0DkOSGEkOkZLdryEmkTK+mFW/pvIat2D00zs0pQ7jLaeqLneCD8sKPpI1Kv2+hmDZ1FQMeelS+tGQxxyy/9CX0/+dd0DA61vpeUlgaUk3VKS4s00xBh1UL9UhoRgE3dcTrjQequ4DPZX6Dm9RHAxtrVxhXp2Hm/M5Ov8ZWDMzw1ln1B19nT+XrC+RF5zqnjvPdMgv66z3JQw1dApCeyUtoZCEhQElON/BpBOamEalkiO4/TsVbqHI6fuoHvu7cyv2+KUdbztLGLqZklcictcifiVBcfxzBtqvUeRh5bS7pUIBvo4OF1e/jopKT1LwVETi+WKdYdTEPDj5skShLcRftU6XWTEUmsYkQUEEmWctTitwPwlK1T9yB3CSDy6aPSobTHlmMx3tnOTMPmKksjjqCIzVxbgYYw0YGIOExJUfax7io5S16X3jGCPX+IKT/Ja5e70IVLzunh250LGJb0rVnortDwfbJK/9BpDpBMt7Pnre/kXX/7UV73gf/BhmtuQDdeeBPIJhC5IhFhfmEey7HBh4EhuTgtFaQwdWNPEm3dLYwGJWMWser09EgNiO/7TKouvNGawcmBMoU2OTZ25ZRpWY+LpzRBETdG/0yNa7r2EdQbOLo874BtU1FakWp0kkR3gO9bFkII+iNyXC6kJBv6VJ+cVkejKdqKeQA2j1xN3JQC55wh37VYpcK3cjfynVBoFRDJEsDj/bkCX5rJ8dE1V/DEHbLiLJqXTq0egs/wKrycwO6SY6k+GqIaXBF6bpoRLEfmwdd56tBdHJjbhqk7rL1lL4W8BBfegPyuFa3x81d+hCvqBwCYCutE1JofQb5Tc8YitbA87/ZinjGxBs/TCOkeo51p8lHJ7txQOYWVPAh+nZQZ4t0jf8yNR97PuuwuauEeGidPomkGHe2yMWLTaPFC0dXVRVtbG67rcvLkyYt+dmpqitHRUTRNw7KsFiNSqufIxsI4qlFjeyGPAD62fR1BTVBwXMZqFnveNEI0GSA/X+XxL5+5yJEuxw86LgOR80QkEcDX4ivuqsrZUhMaV6WvwrJk+3G90SCk6eRsOQH9qNMysCo1Uy5D15aV9Ex2Jb85sGU7G2+46azv9eflbrkSkSmlmOrqGemQk3k0KCfgizEiQohWeqZg9yN8l56uGoQNdsbPT7s/PZ7jv35yP3/y7RdWkufNCzQvgGMWGdvwb5g+vEdVs2jeuUCkafMeMuRi1tCDeELQb0/DFrmQT5y+lsXZYXafegbTsUlVJGjJrbkaI3wLgcQ7WXfN+3jZK3rQcBit38i7vvoU79n7KD+xrot9KAvsieJFdSJNNqS9MwKaoL8sPxvuVa64TUYkdi4jki7nsINbSBs6DQRPVQ0Khafw/fMfb7Y8y94F2SCvrSpf73hvF9N1i51qcXmcKhsbE+QMuSBn/BLlqly4o901lq0Gvu+jt60jVF3ErGS5sZ4H4JizBkuzCagyWKOjwbTuMV2T4sY1wfXcffXNXPvaNxJTC/6/N5pA5MpElIF1a9jUuQ4ELBHG13VymnwvR7riiA13cCogqQOjboMmx+/pxQpzjtwZp0smjuHzcNtRALbl5WIzPxwmpUsg8HeJe5gt/hLxejvXdq9Y6icbZRzhgS9wAkVOjB/hczM5PN9nbUwCo4V4FEvTeKhTI+vFKZnxFhDp7djKtUH5ri0jH0SsXOZEIYNbDBCvmmh4hBI2v9WeZsww+ErmDipakECPvA+dyqDvXu9mTrGWLYNP4YdANKA0E8MLJfHVhmLXlEEuKOeCTsug4x8geEgQSlRoNm1IJhdIJBbY2PUsfi5M8oicE2wjjalaWDSbZrp6A0sxIu35ItmQ1mJWBtIZpvrlfPNy9zECqb0MB13iyZu5pW8jWU1VzkR7qJ9U59Qpq6QWl+47p43E6hBCPO/0zPe/Lx2j166VZeAJXV5DbEGyO+p1oL2QwweGwgG2KKb0YKlKKGpy69vlszz44CQzJ3MXPd7l+MHFZSByngjHZb+ZVgdeTw7oXZ27cMpy8RG2RdiyCK5qdvejrpiBldSMVaviZra30jNWuR0u8II7xQbdNQ0PKLt5ACK6BCLhlGR/IgE5KV3IR6QZt6j0DMANpa8xNSKp913x89Oazd+Lh17YDrlxRp5nLX2CQHqSemyCO2Yd1pbcVsO7pkYEaLmrGmYDzfdACKqRCKlyBXyYebyToP5SADbOy4lqRJUaule9AiN0FZrextodnbQVxrgxLq3yg2I7b+zfwO++ehvXX9HDPB7Cg32PTl3w3J9qpmUUJb9J6UOMrgi+77cYES0e54NfPsxXDs4QTMlriZeLIATDUXk9j5ZNbLtEuXx+8d7nT3wWH9gQdEFVzegDnZRcj78bDvI2ynwU2FQ+zawmgVu/45ANyOqHcHsdW3Ox3DmEEUJLDbJn/gjDptSlfKVN3utOV96rUiLKhFhkSjVU7IitJf7KN1/wXjzfqLoeRypy4b1CeYHc9eZXE/ANsl6Z6IZryKpnvLYtCMMvZVwxIqLu8JHvScbmuycWKRvyHWkvyMXyUOIJwGV9TqYvFzb0oWty/I8cSfGzV22nPn0FN/c1OzT7VMwQwheEapI5emLvXtL2OEW3Tnuwl4DQcHSN091dlHSd79obiVcrmKoabeHvP0e4IEW8JeR1RapV7NBoiw3pjxS5P6Hx5UScKUPnY72vBd9nnS+Zm3jZYfbZFI9rVwKQ7JelyOYZQcUM0BkZwk1JZqd7zqKs70N4Li996j6unT1B5J/C5OcytLXJ647G8qzpPUB9zuTZ/TeQrlQIuw0QBosdUlgrgvL3dmn9eEl5ntFSiap/sCVYHeytsdAZpGFoPN3p896eHO/LNLgn9E2sxoMtBqga6cZdXMLJ5Whr24OmhajXpymXL27j3gQiJ0+elJvA88TCwkLLDr67W47lmErNhPOLROsWdVPOaV05yfh9cT7PTjW2mm0E1mxrZ8vuHgSwOPHv73NzOV5YXAYi54lIIoBntrUa33UZXbxz6zv5ret/a1VaRgpVZbO7F6diBiAUXdlFN9KbVoCIsx5q50f0+WNyIjod06jPyEU4qMsJM5KQ9HGLEblIagbgpRs7uUF/FrPtYbbVT1GJRAl4HhujFwAidQlEYsEXCkQk65HtkPd/cf030IC7Z5wWELFEvPX5gGJEHFMQ9yVQLMejCEeQe+alLB7sJBlaYY184PYNshx4YtVjHNrRgTs+yo7I1xjSn8TXDJ46FMaqOvzxG3cyn5Tg4sF7T10w3dSsmFkMy9fthpqc3M2uKH69DkqLdLoKH3tsnA987mDLXTVUraC7Dr3aAKbwmbEFo5Z23jJe13P5wsnPAHCTYVGzVSqhW6XbTJ1x32MSwdzUrZwMSR1Fv+NwxFpAM7oQGkQyNcrOPgCMjo1cXzxNRC/Q8MJ8K1NC+Aa76vLdmI9001n5HiV7mZJdQgid0rfGznsfXkgcLlVxfcgEDPpUyiHRmWbPetlFdgKDhh5E+B65x++DtrXMqhRpeyPLvzw+hu/7fPfkChAJWxpxK0TDLBGN7KNT6TcmR7qIaHKcl/QEk1GN3+65g/WRBXqjM4CgFIwRzwrClX7Ap1ou8cr8XvJWHiEEXar7biGVwqsNst/d3GJDGrogHwoTUHb0jlbD1XU03yfKMQYX5II5FMvyzWiYnQ0XM7CBo7H13JV/AGF4CM8nEt7Msaq0uY+Vy5QSqpv0OFSCJp2hAdyM/DPd9UkWJ9h0/BP0zR/C1jR+98qf4lPH3kYsMkCjId/PVGYeYRgEOz2E72PYMv0x2b8LACGaPkUljsalJmc2XKPuPU1FAREneAxfExwYSRDeHGJjSPmPiAb56b+gvVdZ2ytztsbJk+h6mLY2ydIuLl08PdPT00MqlcK2bU6dOnXezzTZkM2bN1MqlRC+wHTU8lbLgRGloRyW24p58H0+N59lZ0ze+2Z1FsDuN27gDR+4mp23vzAn6Mvx74/LQOQ8EUkEcMz2FiNSK5b5pat/iQ3pDStAxK4TsRzMNWsoLLw4FTMAmq4TjMjj1mNrMcUpwMWlA3dq7LzfyR+XE8qxpEvutJx4dCEnj7ACIk1GpHKR1AxAtDHH70f+iFDXNykmpep9s29f0B65pBiR2AtgRHzXwxqXYONgWtLa1cyTOIE8vXWn1Xn34wsr59pMzdimRjSYl8fukAvSmWNXE9ZjOAuLaJq8zom2Lna1y++cVCkXTRdEdQGlWYSA662/J+AVqRRtpo7nMHSN3bcNAbDN0/ipjz7J4emz9SLL5QZnliRQraXlQrS1KBc9syuCW1RdAjWNB8bkf9803EGqLY1hys/HKkUct40rIvJ7j5QN8ucR+T0y8wiL9QIRzefW5Qa+sqJfUkZOg/EQcaVhOlTfTfusZBD6bYcz+lHaVav4WE+NoiVTLeVdVxPbKcfEUYZwhEDTdrK1Nk2blad/ZoyB6iQ+GnOOjqtBaMt/LCUDK/4hVyQiZ+mubnj9rWT8JEtqUU/aBfZ/9bMUlxZZDshUzfbGKeaLDR4+scjjZ5Yp6xJZCgR3LklL+HD6YXzAafcZN110lT4YLkVorzucTg5iLe/h5v7HW8cOLdcx3AjhSB6AVNUlX5Puq32L8s8KpkusOMKU2EKbqpgJ+B4JwyDgynMWwieXSQGQLpdbZbvd7QWWIyYfWC7yL72vZaQyxu/M/DkAkYqH8e6Hmdklhctty0tkoxJI94VL1AIGmdAAXscKuH7Lww165p/AQ+Of9lzDvq6NTDrtTE7dTdCpISqAA7GuMldc+Q2Gtj5Oe+ELAIz3b6ARCOI5il1wHDodCWi/cKVPxaxQqEgg0haS81+5w0AXcKSq8aHKezjJCL5X5xU7/xIztkA12IGPoKG0Hp3KZfVSOpFLpWdyuZx0UgVuuukmZmdniRBAIAAX3yoz1r+BhhLPB2ybeLnMyWqDqC7/7JlSDU8xyIGwQdfaxDnHuRw/vLgMRM4T4XgA31jRiBQLK4vL2YyIjdPRj+f5mEGdWPrFqTtvVc4Eu9E0G1OoTryn58/7eW9aLuZT8TpOo0FAc3BQ/Viey4hcyiND9ZgBWGyXQGTHRdiOFUbk+ffjsabL+JaHFjF4XJuVzcWES27wARb1CkJlvb+e9TikdjamsqgvxgzolM8vrzpw1qrLxMw0y+PjbN4sfSAO9a0npMmpK6v5lEMCz/WpHl1GF5JSF5Ua11wneO37dzF8lRT8RTfI42zFwGk4vOOf9nJqodQ6930TeXm9ERMCGmHbJ2mDngqihQy88kpa5oHjclG7fXMXQoiWTiRRylPx4tykSkwPVHUml584J7f+uePSgOmaiEN6VjmeBmPMqjLFgUiQ3na5KPv6IrWGXGQGbQ9br7E8JcdRtLvKYkOxfG6GXcYBAL6VlO9DNX4nA/V5dhaP8ZLHZDPF2eg2TjRMnkqGiV3X87ye68Vif9M/JK5AtuvxpfkcfzC/xB3bb6bgyetIiyquZfHAx/6BivIjebnzCODzgc89Q9326A+tVJPcXtgInkEjscSxfrDW+hxZkKXunmvQ6QT4qUOPItwC94q7uL77KQwh7/uYFgDfZ82QZIsm1gyyFBzHa5RIL88RsmxcXHYttFEPDrUqZrwYbH/4u4ycHMVANWFrk+/Z4HwQ4WnEjAbWgMuu9rXsaJS4e+EBPvXML2JFlbDVTlKdWmQBOe7a/HncGAjHJ6PVuaZ/mZjZhpdamYM2T0mm7+jmtzM7KEHEghdjfPo0eh16fiVA5nfDLMwPATDQcYr/0XGQtDONqxucHNqC78l3Juo8Q7Re5+SIy/61Al8IimYY3wdDl/e3YGt8eDHI4pjDq2cO8Mf8JgXaCBt5Bm75c/RIiVqoncYJCUQ6Om4FNMrlI9S+899h8sJmfc3qmRMnTmDb9ll/9+ijj+L7PuvWrSOTybC0tNSqmPGsAuBzes0w8Z4+bLVB2nlS9pjamy8R1jQqrsep6qWrci7HDycuA5HzhOw3Y2CqfGRlVdOl51bMVMNyYki/CBUzzWgJVhs2dIy00jON6co5n/Usl1BegoD5sNzJdIdL1JRfQCSugEjLR+TijAgD1zNz6wfA9xnvGgJgVyp+wY83jZJeiEakmZYJDCWZrEzxUEmVsfY/yIJq2oYWB2Hwe6ell0RA6QeKCYNQWOZ6izF5jV41S8xIUVyc4jWveQ1Hb3s1U20ZxusWwxE5kc+m1fUfXkYXMqds1U22v/l2+kbSrXMz2kLoqSA68Or2BNmKxds+8gSTWTlmWv4hasc9otwvzS65kLpF5UESi3FgMg/AbZvkmGoBkXKBsogzGPBYY3u4CL6fK1CrjbXOY7G6yMPTkp7eE/bxlQFaJJZiWt3z3lCAgU65sI8kvsBCp5x4B2wXfJ9nRuV9jmRqLFoCQRnNC9FmgO8LvpWqkSybFFNb6K/PsevYk2SW53DMEN9JX4WNz9xokfHDS8/nsV40VjMizfj5oxP87cQC5ks2IlT362QQfKFx4um91E357LZZZ7hJHOJ9tQ/xV+bfcJ1iMABqdgWvsAuAr12rMdcbR9fk83UbMaKahpbdR2rhD/l6qp2uwgauyEhPjWfa12DU99HRPksqNYuvaSyn69SXTiKAbtXAWjcAPUBbXj77Ro98365++mmSqpLjWFheV3cpQEewwk2do8RqLr916Al84I7s4/Ray5RiqlFdtsjyPx+lrMuDhNTBzNMahVMRvrJhibeO/ApjnWebw9137S7mu66lvZFEmDk8NBYJ4KoNv7HgMvrMtRzYeztj9RhBDW7V5Tga3bURoXkYus2u1P/m+t4JPv9Kn6Dw+ZVwkZds/hLNKa/uwe/NBjlS13lrscRbZ7/Om2fu5Z+8/4IjeglElxm4+S+odHa0GJFAoJ1USjJUSyc+DJ/+CXDODwb6+vpIJBJYlsWjB47w4e+e5pmpPOVymf37pb/Nnj17WFhYwPd92kz1rpfkWDzdN8iOV7+ulZ65ckymeD4/Oc+286RnLsePNi4DkfNE0wskoFqKNxwHx3Hwfb8FRITVIGw75LVms7sfvT6kGSuVMyXo3k5AqMqZxXN9PKyJEhqCuZDAduRuvDdUoubKyTKsSkgjz8NHBIBAhBnDJGQJTvUPAXBlb+aCH28CmxeiEWkCEW0owlJticM1HdPrxgtUmEtIUWIkkMIUgu/kSnw3W6Jak7tchKC3LheaujLQCtVy6GYa167TKBZY2y21BccrdYZ9ed1z7dLW2p0soSMns1xqLfqqypZmBNdJ8PZLG3sY6YoxX2zw1o88zlyhztPjcrzYUXm92135+0aXBAReWfXlMEL4PmzvS9KlLPGbJbzxcp6iLo9xk9qdP1o2yOZWdpBfPv1lWcERcBmp1ag4Kq2TbmO6LgF1X9Akpuzk5/0U6bSsCongkPI89mrTCCuCbvq4yToGcgFueDsYp5tlQyddkixKd2WB4HHJuJ284aV09HcyrXbGz35v5mKP85KxaNlMqnPepYBISNfYoQTQTzoWlUgKgKReo96/nnJEvgOm55BySlyvHeEdxn28WnuM7vJ467en3Qq1ZalNeGpE8J32NFEFEl0riuFXMbOLmNY0ztgDTBZexp5+KVpdjKRoW9xHaeYqenol2K/rIWqLcmHt16WhWEFlaNsX5bN3e2yOb5bajqFsidsrVa7rOcngbUv8/Nqj/OS6fWxNLdK1ZJGqNhBInXklZ1JS1u7B4iBZ8ySuJp9feECOyeBJjbmnkiw7BgWjxmjl7MX0qWGJFNpqvRjRk+oeJMEEP97sSl1jKif4qwWPf1wKsKsin/up9Ea6XvbHJHsPUHbSfCeagjaD3+yu0dehITSfel0+nwdLJpYQZLJB2osmBh6/d+p/Y1VTaOlfpVZLEUzO0njnOLWJ4y02r7NDCsYXOwJQnodnv3jeMaFpWosV2bvvGX7/G8f4s3tP8Pjjj+M4Dv39/QwNDTE7KzciXTGZHvSrOWqBIFpfH7tuua0FRDYuzhKqV8npJgnlL/LvBSLL5Qaud+HKn8tx6bgMRM4TTSBiOICvukdWKlSrVWmq4/todoN4LEEup2zAu3/0+pBmNAWrEojsWDE2KyXwn/OCWGNyUT+Y0jEX5QLdHSpSUwChJVYNPD+xKsBsZZaI3Us9FCLcqDOiaOfzRan+wqpmfNfHGpOsQb5L7gKjZpxM6bUALEfkohclyTv75OTzr8e/wdjY3wCgebBjWpaa1owoPpCp5igG5SK/ODHKxqhc+I9V6nQtyvNb7AqQ1gXC8VpAJLjrJu7dO8mfH5jAdVfo/uD6FABiqszHf/o61rRHmMzWeNtHHufgpKLn25V9d17+/nMZkSXVJfT2zSsgrilYTZQLFHQJEK9oc4hqBsuuxncnvil/2/f43HEpUr0+5tKxVF8BIpl2phtyou0JGCxPSu3HnJ9mU3WMuYAE0gO2w5HwGI2sFOzGuqtUHbnTrLk38L1whGQlQF/tCoJeg/H5KK4NuUQb92+6hhvXt/FMwOVYxGPNNRcGos8nDig2ZEMkSGKVKd7VSfmO7c2XGVMAOSVqONEkxbQqd3bqCOA6/SjLfhwfaEytCBxnnRqZvMkVpzx8ITjY6xMXchp0rRhT5X3odZ31tV5YjvLN+bXsDJRoDy3jC41jRorYibuJRhXAJIyXlQt8e2ILkUCS+YwEJG1ZyYj4KZf2a3MMv2aefy6O85cLS9wVHSWasQhoHg1XZ8IIcHL9Zg5uiXNmIMz0RDt1S6ehNgRt1ZOc7PwOALodggHJdgZOCvAFg0fk+3TGOrvSI12YUN/vRY/I8xxvKB+RlKoqqdYY7anjC7CXNlH/4h4ylRkcYXI4MUDnDR/mwY1pxraEeEe7RcIAJx/g0N4rmZ7aguNLYAywfaqD/Tl5/Ro+v33qb8kZNl977Odx6jG0ngJLb8/TmJHgsEMBkXzSxDYEPPa3F6z2a+pESvPjaHhc2RflySdlKf5NN92EEIK5Ofmut6k+QX49z2hvP1cYQRxbQ6j5TeSWubYs3+szkxNozhKPz+zlsyc+y58//ef8wkO/wMHFg+c9j+fGr37+ENf9/v08cPT8qfDLcem4DETOE61+M57R0omUy+UVNsSx0DyPxOAasnNy0nwxSneb0eo3Uy5Dzw4MMSU78XoB7PmzUX7jjHz5DqR1jFlZcpqO0QIsTUak6ax6KbEqwEx5Bk2Ttfsji3PoF0lRvVBGxJ4p41suImwwFZHq+/54P8mFm9HsMGWa3VYj/Lc13ezSjnF37bfxfXkcH0hTBB9cYdAIBsnU8uRMec9mT55mkwIixyt1wsclMJhN6WRMAfjoQmo39Je+hp/NLfLHuSy/e++KD0qTEbGmSnQEDT7+09fRnQhxerHS8nUQSkS4Zk5R6gqINPvMzNryfr90c1frdxOrUjM5PQWAkYTbVbO/r0/Lneveub1MV2YJCZ8b2vpJFR3KTSDS2cGMqnDJnzqBX5WL4zxtDFcnGAtJPceWRhBHc8gjx3G0u0bBPgG4WP4mHotG2Xqik2K4nfXLozy1LIWuT1x/K3VNJxEK8GzQ5Ssxm6+kLw1eLxbnS8sAXJOQ5/bEXIGy5WII2O7FQUB2QDIO4Xwe29O4UpzijN/DfC2GY9loKIbPqbExN8Gr9srnsuAv0qbK830nxuniY9QaHl3WAG5tkEerDeKTL+Um1Qjv/v6rWDOZJbu4lmCwgmE7BEuy8szo2MD6zVczm5HVFk2xqpuASLyIGXHxfDgeMPmKmebw8S7++fSVfHlqMz/dk+FL297HUkeQmZ4Q5VMGzpASkFc9Al6FsqJakloFJybAgcCYoBQ0GVGkz4legRdaWcj7lvJ4wiXoBkkaS4DPotVGvpGgEpTTf6hWZSk+BsBQYQTPqTF8RHqtfK/8WnxXJ9pXZDDsYHkQ+IZO/sMdWM/6lMttHKjqlD1BtJFkMPsSjhYy1FwDF8ENxUOI099h1ulj8nvvx7OCWBt8nj3xi3ieTSSyhpifxheCpbYAzD0DE49xvhgYGCAWi6F5Dj1akfbaJI1Gg87OTkZGpKlcE4iElcmhV8sxNfh6tn9sjIcefgpro2T0suFlfP9TpGd+lVLlN2mf+QXmxz7I7zz2O3z08Ee5f+J+ji1fvKwYoFS3+e7JRZbKFv3pF48V//97/FCByB/8wR9wzTXXEI/HyWQy3H333Rw//sKMrF6MCIR0dENDI9iyeV8NRFaX7uYVEHkxKmaacXZqZgdCeAQ0uftZ3QfFd32sSbmTOpDSSZTypMwa9EpfgmAkim4om+zn4azajJnKDI2QXBy3FC9uAlSwFjHizzBR2/+8rq2ZlgkOJZgsywm/L9YHRZ3U1K3UXPl8ErUY8YUa9xifIESDYkjmnn0NhO4RVLuscixGpppjXhlYzZ483WJEJusWwamq7FJqgBnREFTRNLmQPzQe5uqTEkj8XbDBl+bltRrpEHpbCDywxooMtEX4+M9cR3s0gO36+Bq4qvHa2mULBBgZxYiU5PMp6CG6EyG29q6o9eOrUjPLZhpNdR5+eVmCgEMVi7Hlg3z+xOcBuCrikAh1Eqm5LUYkkk4zozQiW7o66VZpn1mvDdN3KRryeFdWJZiaVU0Co91Vpmsxgpr0D+lpXEdyapClRIJrn34Yx9fpihbwh+S5zrvfAF0gLI9PHJvH+Q9Q1U1PhysSZ79T1yhG5PSCHMNr26Ps9kYwfJ1yWL4D4UKWpxu70IVP1Q8xUU3Je6g0Q8K22ZSdYNu4T3/Fx/U90kq3YSiwB3AqfAV4YSxhMzZ1HXsyBxF4jCd6eKh+DHvsZjTNpn15GeH7iHA7RqSd7ptuIavYmbZy0z/Gp9Bv8Y2Zn+U38r28sa+H38nEOGR3s2xFiUZdZnWd+xsbsfwAjZCO2+5R65DgKazKZMsl+e/2qGQ5AmMCYQseWzPEYNZE+D4LacHihpV7Pzzjkg9JAN9hpQlG5Xg7sryRckC1o3CLFIwsUTeMKGfwvTIbz8jnfjQySO6xX+dgMcSTFZ2jD2t0fE2nV2zg3pvfQLnSxncVG7ItdyUBcxOOr/ORU9fwiYDs1XLbkS/R3gmN3Bqmv38PWJD3D3LkyC/j+y4djmInO5S+5fH/c95xoWkaA+tkp+hhfZmZExKI79mzB03T8DyP+fl5dN1Gq8ox4tdyPDTyMB+57pf51aWf414hv+NrDY7VDmE4MwgcfHQco5srunfz1k1v5deu/TWu7r76vOexOh48toDleKzriDLSdX436ctx6fihApGHH36Ye+65h8cff5z77rsP27a58847qVTOFVH+Zwpp826CFm4xIqVS6ZyKGb+zH9fxMEyNePu/v9X9fzRaVTPlEkTaIN63ohMZWxEO2nMVfFtQNuB0XCNRztMTLlFt3wmssCGwohGpWM5FnQ9tz2ahukA5JoHIdqd+0XMt8izh/n/jodnPPa9r02ImgYE4oeEU02Xpf9If7ccrWqQmXorlKfdbIajunWPPlf9ILPNmXnPdP6NpEmzYpiCqOtaW4nESdpU518HUgixPjdNmGnQq4FWM6HRbktGZSRutihmbEP/6nRluPVxnx6k6CHjf0XHuX5YTe3CtXMjrCjgNZ2L8y09fSyJkEO2Q59Gp6SRtKXDVVHl0kxGpmCFu25w5S/DcYkRKBepaAK8sF8zOfI5NkRA+gg8d+CsemLgfgBvjoJXz6B4tRsSLJbF9Hw24dng9P/O2HwNgFpnGaq/L8x5y5Pl8p1zEc3XMiMt8SCOsSaOyO7M3kA92gOfROSYBYf+aRbZF5RRyKghuu2oyNlPmgeylGwGeL3zfX+WoevYOsytoMhgKQFk+85HeBOmdvVzlrKOqKmaitTJ7p+KU7QAxUWWyIq+vLSh3wppjsTE3gQDuQIqOE0jwHQikW2nOCVcyfGFziWMNnXXLO9naLnfIx50Q31+zkWotReeiZMvcNsnITAblfU3nF+moybFQi4GfsJnt2ISh3GwdTbCgnD9LRheeE+dEXWO6Id8jc0eDktIVOUrLUfTkOEq3SSYzcELgAcV0iqf6e+gtyff3+PqVMTQ8C7mQfG/aqj34UZmmOrK8kWpIHl+z5by2pbaZRKUX3y/TkVskU8zj6YK96Qyfzhl8bTnE3cekwD1sGITTG5iJlpmwdHR8rk2sRWgJivEeqn6Q/bk1jIb6aG/keZv5BVx8Kkubif1zCjzB/MLXOH78g3SU5XVV2tKSPzz2dciNnXd82HGZ9lmrZ6lWq6RSKbZulRb4y8vL2LZN/8BJ9JoSq9ZyVEMxfOFjegFCXZIB7F/UecmhDl6y9Q9Y7v1zyh1/Ta73T3j59t/l16/7dd62+W2sT126aee3DksG5hXbu1+0YoX/G+KHCkS+9a1v8c53vpOtW7eyc+dO/vmf/5mJiQmefvrpS3/5RY5IPIDQoi1Ts7NSM0qoWotJGj3VHUG7gG/GjyJajEhF5Yd7d64Ym61iRM7Sh7g2oUaNnnCRWlzuMsKrur82GRHfh7q9ood4bixUF3B9wXJKOqpuNy4+pBq1FABLjdnndW3Rq7rI3LOL2O4+pktyQh0M9ePbHmajDddT4r3oAtUDiyS0Nq7b9vvoerhlamaZGgnk4lZMyoWmXF0mZqSo5OexrUYrPbOY1NmijM6OJXXqvgQi80YXSUlmsO2ZEtpMFceHnzk8yuP5MsH1csFb3Xdma2+S7/zKrfzC6+REOeyrlupdKzv9pkakYoZ56eaztRWxdqnfCDgWoUaNRkMBztoUr+yXLNbXp57E9hwGTJedPTejLUkAWnHk5F5SC2t30MTQBP3t8v+rhCh5MXpLcuEzlLPuaKBINSsne7fN4svJZ3Bx6fMymJE0245LJmtzYoFsvMrNQ3cBcMLdhrMmhrUjjTsY5V9nli/1aM8bozWLvOMS1ASbo+eC+2uSUTTlbryxK07Hy4bZ5PZiB+Q7kIhEsB2P7y+uYY0/y4xakLrCElgE7BrDBbmQb1u3C6ClEQmG21rl66Io3/ukVmTGtdAnb2WPaoT3ncErsObHeGz9NjoW5fgoq0Xrqax8B/tnxolZEpQfVSmQ6398mf4rrwVgzXIQB52Y0SBf68D111DzdfIFee8jGYtSE4CEFskaUSxdgO8T7JaLX/CkRjVo8pJr+7BMg4GaBFsnuuRc5AmdgANGQ84FbdUetNABAI5kN1JW6Unqcl4reTXS9S7w5DVsmZbP8Gimg6+N5/mLuTlSKqUaNMpsKriMJeR4uyLiEu3O4+MzGt/OJ/rezBPuCL+97ucAuCX3GSqKWbQnhui8dwAQTM98kgV9imufznF9528i1t8mdXlPfPjcwQEcLwep+ytp3d27d6MrL5C5uTl03aKv5yhGIwVIRsTteBXveOp/8XMH/4xfevnvAdBRFAxNRnmL3YFndNJQXjvfOXF+w7TzRdVyeOi4ZJtese0/XrL+/3L8SDUiBeXH0dbWdt6/bzQaFIvFs/55seK5/WbOSs3YsnS3aCoK9kVMy8BzUjNwlmDVWXbxlC6j0TQFU2kZAfSkfGqKkm5OwgBhU2+V5l1MJzJTnsEx+3GNANFqhbXpC5fuep5PRVHlC9VZXO+FaQmmynIBGRTKyjuo43oSYEQTE1hiieqBxdbnm14itilo8+W1l9pUf5faMsFAB+CTnZpkvTIPW0zqXNcj78OxhEbNU+V/jSTdyqkx1hbEPJxjjSOoez5vf+YMJ7vlomlPl/DqK/erLRpgRqWP1tcks9TUhwDkFiV9b4XC3Lh+pVeOPP8gkaS8X/Fygbrq3lrXlnjZurtJaCtM1fUxl1TqOsKVuqy4cORknQvJ7/Qq35ZY0CCuFpMx9+XozpC8fywRcuRkOldWpbFdDT5rrONgUFYmbdZd+hYmERrclBljQodaWVLdi1o7fluQwb4yBHQeXC62qnVeSOwrSrZ0eyxMQDt3ero6GUU0GZGuGHoywBljARGQoFO3bJxInGcL3YzlUzi+TkS3yATlWAi6dXTPpR42yHapRV+TQDsSa2+9A67C9B1YxHz4Xi3NTejEzRLZQJKBI2Mc6R6iTc0J80nZ5+ZpBT6GJ07JqisB+5VpXmP2BPEtOwBYuyjHS58oEKlYaJoEMsNPl9FKYIegFlZCXSF4Ni6BfsR0IFYHT8McFdSCBjf25Eh2ddNfkOd+Oq6AiCafeaogBSRttT6M8Cia5lJoJAkNy9RDquzRY/dTdQW+7+MpILJ5Ut7n/R0BDN3jmnoDQzFgQbtIOpdl1pCbg5tjDnMs8vmoxXeD6ymaSQpanIlAF/e13YDhO/QbCiRHugh8K8vGDb8NwERimeW2ACLSBte/Vw2Ef4H6ufP/UxMFxl3VTTkaZdeuXa2/m52dpa/vGEE3gEDH91wWQjptw8NE3SRO3cMOpuT5qyaN1c9/km2xML4Co08t5qgWL97EshkPH1+kbnsMtIXPSqlejhcePzIg4nke73//+9m9ezfbtm0772f+4A/+gGQy2fpnYODFs9gNJwK4RqrVgfe5GpGI55NtqGZ3L2LFDDwnNQPQvR1d5NBZAATWVBnf92mMNd1JdWKlHLrw6Nx0FVXV66RZMfNHZ2b58mKeUFRZhF9EJ7IhtYE37vh1ADZOnCGYuXDFRNV28ewEvqfj+A4L1YXnfY2+77dSM12eXCi1RADPUX1m9Br5gfupPDHbSiWtdldtV5UvVWWQ1V7N46gmeQvjo7RnlaCzK8jVGbl4H03oWIoRmfXbGFGlt7t2dSF8cJ9a5PpklJLr8bYzk0z2Sp1I8z4343hFLk6tiplVrQCW5+Sus7evk5B5brn16sqZuiafsxOvkQ7t4HplcBYQPtfEg5hGgmjVwfJ0XF8uRosheay+UKD1m11JuQiecV+B48tddE9jkW5HLswn1SQd7nfYVbiGA0yyTz+DKEvdQG9XnYTZYNYweHziy0QcH18xgq8f3M6NqRge8MnZF9ZhGc7uuHu+uCoeRlQUsMvEyOfz7NdGKShwFbXq+Os24wvBdxckCzIQzRM35/GV12bD1Cn1B5hUZn0hVdJc0BoQjVHTgjhKPNxnGbQ7Ae7HpmPqdm7olSXTo3on1xw5iOk41INBJmMRPOBZZePfNStZi3LQ5EhDJzX2Mjofegfak3kA2pfk9XXkakQrFaJ+BnyfoafOENqvcWad0hv4Pg46XxWySiwdV/d0PoRmCfSYi37im7z+A7/Fnk3SqXTc1HA0EIot7F6WYyxd7UITHnpCAo3lpLw/6TIEgxvpKg2BX0cg70t7NkUm7+Bqgk/m7mB+fwKhQJtWKTLOw3jCp8OOs3f8lfyfvS9n1PTQfLh1cR/vn/sapVAH/334fVjCYMSUzRir8X58y6LTvpHh9b8KwOm1UaYaT8L626F9A1glOPBvZz37Ut3m+FyRI24XHZku7rrrLkxzxRhxfn6Uvv4jGHUJOv16ntG+frakIiQ7FUOojPBM10N3PU6NneJ1yuUWYD7dyf3/8pHzDb1z4hsqLXPXtp7LaZn/YPzIgMg999zD4cOH+dSnPnXBz/z6r/86hUKh9c/k5OSP6vTOiUg8gGemW4zI4uIitZrMj2pWg0R754va7G51hFd34AXokbuuVifeyRJuroFXtPDwOJyUjEhXqIS+/hZqagcQTiRZaNj8xfg87zkyTm53hsbuDL83McdXF/Isn4cZSYVSNEy5W9s4fgajq+uczzRDuqpq+I4ECE2G4/lEvpGnYsvdcpsjdx/1pNHqvNupV8kPPERjfhl7St6HgCnz8Zap0aXJSaMSlBN8ppajEkgBMHPiFMHT8reXEjqbKhLIzIc15gKSYakbnQQ8OdncumeQVMRkqdDgPdEkO2Jhlm2H92wJMBcSrQZ9zWgCkTWzzYqZlfFSzsrPblx/fmp3pXImT0WZzjkdPsxVeHlmgJGgyyuTNmu6XkalcpJI1W3pQ4KRKDOuPOfeVU62TcHqgtJIVLQQGj5XleUkPWWrUu5oGdOo4QmPfeYoS2sGqXb2cU1avpczhsH3p75H5/KKCdWWaJi398r7/snZZdyL6IvOF/tWddw9X8RtEEoAXA9pTE1NUdLqzKvmbG22S931cDp6Whb3g5ECmn4YXy1addOgsjbEqeIkmqcRMOVzeaT4NPNmiDnVsybiZxmodhP2NY74DuXsRm5Ly469T2Y2c88XpefFUkcHFbPM0aigYgpwPNyqYkH0IG+ffRNdJ96CQMMoFYlVDCLVABoe0QmHaKVC3I+zeew0wbkikX2rFjUhOMRO7Ira9CTkO+OdkJ8JpoB6nslnH0XEO4i5YRwEo92gq8qxtXN1bK2B7uska504iTwADy6pqrkyuPEaXeUhfF++O45mIkSALZPy3nxr3c1kT0TRdPmsG8UCh9KPALCweCffHLsD19cZ9OG9CyU+8Mi/ce3BA1Rtg7FwP/+n/8dpM+TxlpOyx9FnHtnLofCbWDMl59jR7BdwvCpc/2557U98CFaxpvsn8ng+JNJtvO+972lpQ0BuVBD3Yxg2YVe6Jfu1HGf6BtkeC7f6gOXyIMISlARcj4ouuPr4MzTvuKsbfP/oMUYPXFw+ULddHlTlui/f1n3Rz16OS8ePBIi8733v42tf+xoPPfQQ/f39F/xcMBgkkUic9c+LFeFEANfsaGlEltWuQtgWwvdI9vW3SnfTL6KZGZytEfE9D5IDYIRXdCKTpVZaZjZSoaELkqUCPeESrL25RUVG4glcfH5uoJNtsTD4Pn7M5Mv5Ij/77BhbHznMbXuP8d9PTvGtxQIFtWDtV3T6xvEzGJmLABFVvaG5komYKj1/INJkQzLhDFpZlV7GXYSvXEMj3XhmlULv9yk/IfUnpqLrbUPQq8nF09JD2IZBpppnWYkF506fwTssUyRLmo93MsdgRXXIDck/3x7uwweCAY1oWueV2yVwuPfgLP+2cz3DkSBzus89V4WZGV+hdsuO23I2XZuzQRMYSry6WGqAYrG2b+w773WvVM4UKPoqbdAOjYkzDLRfx3szDW6JO3R1v5ZS+QjRVRUz0VS65SGymhHpTkgNzCI+MeNLLKr7tK2kszm7mU1LV7VavHc1JuiZMNAsC98M4Hb08A3/ZRxlPZH2jTi+Q6CxsmHYHAvxio4kaUNnumHzUHbF7v5S0fA8ni2f3XH3uXFqXi6UftTk6VKN6elpGoaJrcup7LainF/q7T14yml1IJoHbRTXkP9fCxhYm3s5lj1GzEqjB+T4fXh5L09aS8yF5MKS0CeINlIIBCFh8SAO25auZDh1Bk/oPBKXjO1iZyeOWWJvXJ6DVrSpGwnQTLp2vpO7c7cCsDDyKY6t/zh9SxIIZrQKhg2xSpmkJ3j196TouMNqINyVqXmPZ5Gx5XXH22TFTOyofPdGe+S4+d7+wzx84FEGa5LVOja8Ama681DRpX9Me7Wn5SdyKHUYD9B98BYOkymtwVdpGV+1bdixIMf/05u24a03CCXl8/nKxiglI4/nxKgUrqAjtMzP7/owrx2Ypa+i2MdIhJ+NlRC+x/9e8xM4phwLTqgdHzh04BDvOXSS9WcKrB2r8Pngb2MYMdj5FgilIDcKJ77duo5mF+ur15yb2s9mJ8hkZL+ZruhrAClUPd03yHAowGjQx8cnN1fFUKytacr3cP5rn2N3aqXiZbazn/s/8rdY9do5x2nG904uUbFcepMhdg2kLvi5y/H84ocKRHzf533vex9f/OIXefDBB1m7du0P83A/0IgkAnhGHGGfnefWrAbC9wn3DeE0XDRdtGi/FyuC0RUat1GtghDQvv4sRqQpVD2WkDuMRDlPT0pA5yZqqoQ0nEjSEwzw28N93H/NRnYeLWPuX+bl0WirxPVIpc4/TC3xzsOjbP7+Ye586jjHynLXtHFyDKP9/PofkGZmAkgrIDJZev6MVxO09MX7cEvymcxFlEeKCDIy9NMA5NbcS/XgPF7dOSs1ExE1NE/ZtsdiZGo5poS8b9npcYySQ7ImwUfxeI7NqjFdl5BUeKioRIzrvs3PfeFKNvXLc//2s3NEEXx653p6TYPxmM57ej3yZblzPFGV96ZT02TFTEcYoQS9Dx1bIKqqjNq7ztaHNGM1I5I3OxGODzpUZp4llZLCx0Cgg3TqemrZZwjY/goQSbcxrTxEmh1sfd+nvSGvc9G3iOlfp6aFaGCy4EbYUpCmUTVLLsbR9kmic08ROXOI5OIyJgbLtPFpXsPQzI2019spmXKcCWBNKEBQgzd1y3Hw8Znnb/f+bLmG5fu0mTprVgGn1XFiXi5mfszgqUKFqakpKkH5/sUsh01OhozXBkJg9w0zlE6TMutoYhZXW2FEatu2kq1nSTU60QNywakAZ9ommFMVNq90j2KoniWGUeQ+bBKzN7KnW/aa+daG6/CBpc4OHLPEM0nJgoi8RXsoSmT3LxLL7MDG5a8G/oE/iT7Ilwsm/YvyfDtUmXK0XCFdq3DbU48CkB6uoDsrDFZo8qU0PItgoIIRL4PvEz8un+HXN9xGiQhLdXm/4ppkA45LyQqNgBy3wZpMi6SrPRjGESJGAz91sOUC2zETIOCFcMjL61X6nF4rx/rpCVzdYO/NV1PSI/zdztfyr3vk8/XyV3NNeIL3b/oYuzKH6R6YI6TEr5VolN2JNOs4RVUP87nB1yBwcQnjpyLckltgd9CS42aiwbQpK48IROGqd8r/XlXK23QpvmrNSouFZpw+/SEMw6Ze7yTiSwG2X88x3b+GB/ZO8ycnpvh22CY3W8Hs7FTPVD7b0bkp7m5fBUQGo3xhzWG+87l/Oec4zfjmIbnZedm2y9UyP4j4oQKRe+65h49//OP827/9G/F4nLm5Oebm5lopjv/MEYkHEEJr2bw3Q7PrhGwHOyV3XqmuCJr+4vrCGaaJqcoXWzqRnp2tTrxe0aL2rGR0nlBlxolSjp5N20GIFUZklVgVIKkb6At13hyO8fC1mzi0eyt/v3UN7+htZzgSxEN2rXSAdLFAnwbCuEjDu4bDmwnwhorckbwQRqSZxumP9eMW5SI/H5AASjNS9PS8HsNIYkcWKKWepnpgodVvxlJVMAG1yyzHYnRWc4wJE4GG51TBrzAkDIKujzFRYnNBApEeX05+c4oh6Bz5Oj/RXuPaPkF/Oky54XD/0Xn6QgE+e+UwadvneELnHQfOUHO9Vlpm2FM9ZlbpQ+4/Ok/Uln+vx8/vQRBXlTOJUoHl2ACBomSDKtkTZDKvYHDwZ9my+U9pNOYIqrbzJVuJ+VJpZlYxIpXHHuP4ziuIHpT3csFbQhM1ak6If+TNLOhhfHye6niKaQU8o105FqI2wve5zriat9R3s9s/jolDI9vgtvnd3FUa5U2NT/J+/w959JEbyOYe5W0qPXPfcpG5xtnv0IWiqQ/ZFY9ccHI/qYCIFzN5KldkdnaWakA5hFo1fOAWeyPC17DCYbq6rkMIiIgFDFX9tRyNUYhL5m6jvqb12zUPyoHjzIclE/tSMQqKtPeCC5zAY8oxeKkTJ6jXmQ10ciizkVwqhadbHG+Tz3hg2eJ1HTeit6/Hcap8svRNvhXbz+G6wa6yTfeyAjcVZSjWaDCwOEvQtvHTPoFOGycgn5tmRSmfluxbOi4ZgVjeRW8ILE3nrXe9icPGdnn+YZMd9Y3yPnXK37ZUZUyyOAZAe7WXlFXkhthRhG6Rj0nAM7Qkx1lZiU9NXVXHVIu85ClpMPaxzW/hNuvP+NqmdeiRcfA1fnnDo1zRfpKG8qHpbptqAZFqJILj6GzVJYvzwMBNBHTlvbMtyabZKT41ogBNMMw96VUeU9f+LAgdxr4Hs8/guB77VQPJq4fOBiKWtUyp/GUAXOeVOPNyXnDqBYyeNXz4uzKdttbRyc1VMDISiAQ9Hx2BIwTr934XQw25qfCjTGVqPD54/lYFluNxn0rL3LX9crXMDyJ+qCvo3/3d31EoFHjJS15CT09P659Pf/rTP8zD/kCi6a5qOj64K9oIoczMSgFlKf0iC1WbcU7lzOCNaKKBKcYA8FSlwcMd8iXuri0Q3/ISgLM0Iquj6SXSdEPtDJi8NpPmjzcO8P3rNnPgxq387eZB3u7X+ZV//XvMi+hDQGpEDuHSbf9gGJEFQ16raSTR9Qh9fW8FILfuXvDBVEDEDspnGfZWTM066kWmPJt4OCXvj7vE1nSEq7IuugeZokPQa9CuHBrn7TbAIxSQi+VAegd375K0+Jf2y8l7fSTER2phorbPXrvBzz47xhGValhXlYtgUx9St10eOT5PRDX50i6QhlxtarYU6SakUkbVyhiaZrJh+Ndob99DqfwskZoETyWlwQklUywoXU9vwGD+D/4QvX0LGUOCngW7zmkG+bb1EhboJOxb6LUE4/FxHijKSTjSUUcEfNpCHqP9ayCyyLqOBq/Y/i1uuOEBbtz9aW7f8BCvDXyOq3kS216iUNjPSDTEdckorg+fmn1+pbyXEqoCHFepGWIGlaUlXNfFUs0MQ1aV09ocST/ClTG5IN8vlviw/xaeEDuIqfe4GA1RVv89IOT9dewglejNGNbPYBMn6Nv0CNlK3sejEZbj77tenZ7pl3CdYkXu3XUrpgYN3WQhYbA17/IPWYOoEcerLnH4yIcQy8fRVcXVS+YEpqtRDTrE7riZpoImXS7iA/5IlUrMAOGjOSap5dtY8uQ4TyalXik2pxitSII95cc5Fb4KgM3M8vLKWjQgFxQsxcFTFTtdy1IY3l7r4ScWX045KUW3i8p8rS8n5w8beQxNl88gvLDELftk2fKxSIZlM0Vb4gEAdkc6GYrlaUQMyiUJPEP6aUKNJhCJ49ouV0Qk2F4KCsY0CcIa6Qxm/TheUZ6XrdWILn905UEn+2GLFOjyxIc4OluiarnEQwYjmbMr88Yn/gFoUCq10d5+G86ivF+LQaifKtFwPK5Zk2bE1qiVbEjJ+SdUb2Cm5PWP3vd1Ngfl2GpErubq7mv5het/mfPFI6eXKNUdMvEgVw2ey85cjhceP/TUzPn+eec73/nDPOwPJFr9Zny95a4KK66qOeQi92I2u1sd51TO9MvJqZmeAUCbYzlkoLkOG/wZxLpb8H2/BUSey4i0+s1Y56+a6Q6avKG7jd+YH+WGw/tbudcLRanhcAyXDgVEpoovXCPSH5NmZgDLKNdVpXEY6H87QpjUksfxti61UjOWKbc6MV8u+qVEDN33iNYLBCJtIIJoWoOr+pNcvySfdb5k0dWQC6jjm+TdOHqwjK75eD6EghnuvkLm4x8+sUi2Is/pijVt/OW+GkHP5/7lIv80LVMTa3Nn95h57MwyorZiv3++ZnoAiQ55T2PVElktTrgun0XDP7viqFR6lmhV/l3ZkWDHVZ2UQ5rAuO8+GidOENj8ajrRAJ9E0ObjvI4GIfqY5ced+9hRtzHdIBO1Mk41iNChb/ccXa8qkr7ivzJ6068ztvUguXQOw5xBCJ+KFWVxcQ1nTl/FwWfuYnHhCgB+QrEiH59dxnseotX9lxCqup7P6UW5WKztjJEpyd211gRrNYcDxhg+PjuWu1mXlhqOGdHNw9xAtkemXKqREIunpzFdk5RKvTj1AOX2d1GzhwDodZaY03cDkA3P4QflAv09LAK1Tu4Iy7FRWp8momksJNLcvODw909WSaNhV+epPvxHZP0SAd+hd3oA0/fJLMtrm+6sw8v2tK4tUquRS8QJDVVbje4016A7cjfznjxWIiXBYXhM3svpeCfXfFbnZFEyftdXvwe6Sb8mv3+iT6C7clwOLFTB94jXO9iTv5plowBoLKel0LwrL+c7oRphCtXbKJRbZmBpnshSidBcjXeFPoOXlmme25QGpxyKUFbur/X6KBryfBvBdhqNBtcmJXBYEkHGVTok5wzQdUUeRzm42oaGZT0HsDZLeQ99lsMnpK7lysH0WZ5NDWuJqal/BWB8bBe9vb14peamq5vJ0QJCwAdfs5V4Wh7bCsprC9dq1Lslsz2TX2Lu9D/Ka4jewruu+VPigfNbEbTSMlu7X1T/qP+b4nKvmQtEMGKg6QLdN1uCVQDNqhM1A2Szqtndi1Ax06hWOf30E2f9WavfTNPUrH0DIAiIFbqzEpALf7xcpC8FtK3DqtVwFdAKP2dXHgk8v34z9oJcFM2uSwCRuoML+KZkTvJ2nvJzmnRdKJpApC/a22JEcn4egKgCIsFgF11drwRgaurjBJo+IqorbEpVBJRT8l51VvOkkkFybe9i3ZW72ZyIcMO8fNaHrAZbqrLSJk8HPgIzISdKS4TRNJPhTJxtfQkcz+frz8hFIrguyRV5lz86UMMQ4Kr1d0j1mDEUEHng6DxRW7IlIhRCBM6viYgkkgjDQPN9ajWHqHpWdqSMb63ol0qlI0QUEKl4SpSpOtL2BU2W//qv0bu2oyf6aTcFN5mjbA8v4qOxi2d5J5+lVx8npU3Sn5NarmZvk/ZNBYLtswS1CsI1CedGEPObKZ34BY5+7Xd5j/6n/H7ot3iyvIdivp10Wo6DV3WmSBo6U3Wbhy8hWs3bDqdrEijuip8f3I8vV7Acj5CpcUNvkq6i3Hk3QnLcxiuCglYl29ZAR+O2uRHeWr+JO7xDbPZPoql0j3AdQkdCvGriVQil02g4YXTHIeLIe5epzjDvyP4lC/FxDEOC3tM6HMfl6vwW/mjPB/mF6/6FRDjIJrefP9lfI+TB4zgUn/g/+I0C1ZQcm2umU+yp1pgupQCY6qxRyyTQkqrJZLnC3h0biRveChAJdjCRHGTeqBAIVAnFsni+QD+hmMpklIRooAmIUmVEjJEIPcs6Ie/fiT5BsJHH0YOEbNAbpxAINDvGTy/fQ677t9ET8rcSVQWUbTn+hZDnGWzkifRH+UTpe3x/6zq64g9j64K1sz4Dmrwn2VAbth2m0QgDPma7nA+sQIZGo0F/cj19vmQ/F5WOZtkeJJhw4IisPLJNcS4QGbgG+q4G1yLxrAQbVz9HHzI+/vd4Xp1isYNcrpeuri5828DD5/MpadT45qsH2NaXbFU3VjXVDqBWoyQ0LLOBQLD15Gk038LXo3xl6fzzku163HtEpmVesf1ytcwPKi4DkQuEEIJwPCD7zbirgIjdIJ5uIzv74jS7a1QrfPqDH+DLf/J7nNn3ZOvPz2FEdAPCqbMYkbmI3EEmy3l6NmwCIVpsiBEMtnQmzYgGn18HXmdeTjwXq5iBZvku5BNxko483ybAuFi4nstsWe5C+oK9+JYEFgUnD0A8uDI5rRl8FyMjH2Rk5IMtRsTRHDwgrYR45ah8Zplajkm60cw51u3qpK/ssrYBLj7J6b3sDkvwsKjKgL1OlUoyUq3jNdMzX1TpGT0RxOgIc9Oiy58n2hFAQAjW5R0wBEZ7GN/3efDoAjGlD9EuoA8BEJpGtE0ySE6xSEQBEafDx55ZyWGXS0eI1uTfVZWHSEEBkUwhjzU+jpFZR0Vr8FjiGYb1ZTwfdtQP8FruxfA9TK2BJxa4+YC0Mn+0aiDO6KRKW3n61E38Jn9M7yPvYfDJ38A5/HqmD2zBsrpwjQwLiTa+svMmjtzwUjZsUE69usYbu+Qz+Pgl0jPN/jJD4QDtgfPrjJpC1Q2ZONekYnQpRmSmINHegDJv2+uflNIOHyIE6RIN7i59k1d8W1alaK5DUc+j+Ro6Esx5bpD3Pv4NriieQsOjuzbDYk3e9/nYGAnkHFBH535swoVhOsI5qtVRtnl9vGUhjQ58Jerx19QxKxIklZXGZ02hzE9WR8haEXzhM9tRI9/IE94kxaWxSpnTA2uJeX4LiPz1wTt4570HcQ2fZEIufou5dioLUuy6Iz3N+8yvA7Cxw0DrGCEahw1IYHaiX2C6NUoxyQwly3JTknNdPtz7XZzAEH5CguFgo0AuPEfQVjt8v0P9eZ74+gQDJ/bgfuY4n47Le/yKpz0sMw/AWKQHD9FiRYxOqdGwjF6q1Sqx2GY2cgSQPj0AWWWhb+Zliss2NDyvhuue3aSTGyQrcsPyFwlgc/XQihi+0ZhnevoTAIyP7ySZTBF0DRAa3/AtlkWEWNDgl+6UabpmGr2kmhxGFJB/dljOJ9dOtLFNuUtfqNrriTNZ8lWbtmiAa1edy+X4j8VlIHKRiCQCIFb6zWiug/A8Yp29WDUHoQlSmR9taiYQjtC1fgO+7/G1v/wjFsakEOscjQhAcgBDTKLpJRAeh2KqL0spR/cVsqTwQkJVWOnA29SIXCiceTlJXio10yzfzXcEX5BOZL46j+M7mJpJm62qV4I6JVsuRKngyoQQi21koP8dGEYU00zRFBvapqBT5b9rgQiuppGp5jntdzCybpGN13Xz8DdUHw7h0Z8RbFHAZSokr6uuOpSGzBXA9ZqdvWgC9k3kmViWk2jT7v3OaYsvXDHMPyc7SDhgdkYQmuDIbJGZQp20LydCPX5+fUgzkir1ECnlsZDiOLfDpzEhRYANawmrPkdIVf3UmiXnQTk200dkWWP1tiG+ktrPfGUZC4N77Y0YxSIVt42yMokb74yw84x83g+JEkPP3MHG3t/iydw1jIn1RDUpXOx1B4mYJ7BH5LkLpwBC8EQwjrMqC9NMz3x7qcDic4Tfq6PVcfcCbAjACaUP2dAVY7spSNZk2W1BNWq889aN6LrOdG0BbcMKrX6GDmrLAUK2g1A6occ6HmbfwCGMoDyubeuEcnnWzZ/C8wVd9UXqDbloLsTG6W4kQJOMzXd8C82OYVblc0lq8jf+bjjAH2oNhh0bobQ/0z2DWJEUpu9w6og8fzsTxDJ9Co0CTkiC/0ilSrriEcKjHJXv3enCAIMh+TuppARySasLtyyn7a2pKeaFHJsje14H9+zF7X0pG1x5z0e7BJYBtbACQzn5GwcCk5S9g1w9dpSFmPyzoFVgPnoGrdnNwZNjPBDxibbPo4V8Ho8eZE7zSFoeN5z0cEISxEwFeimEo1QUEHEHPDxh4IleioUSkcgQm4V8t3K98p42/AjZxbaWeZpjSvB1Diuy+TU4sV7aKHC38dhZpbJj4x/C8xpo2gj5nNQfOktlqvh8WHXl/q+3D9MZl8ds2izk6xLIBavyeVRTEfA9/KrDHQoITdQsau65rS2+ebiZlunCeJGLFP5vist38iIRSQRAi7aAiGjIwR1ol3nFZGcY3fzR3kIhBC/9mXsY3LYTu1Hni3/4PyktL60CIqsoxc6NCOHTGf0DOjd8nYORplB1EXNEApFaSQlV4+cCkUhLI3IJIKJSM8YlUjNNQFPvCNGjOm5OzI1e9DuwSqga68NXfUb0RICqlQegPdx+3u8JoSswIkt42/RF8DQQgko0SqaWY5Q4nf5JjswVsU7J33us26Sy5waGbDkpjkfludoqtaV/f4zyo7LUMpMIsXtYTvRfOiBZkeC6lb4zN6RiXJ2Xk62pdmQPHJX36+pOuYBejBEBSHXK+5ooFyjFdkh/lzBUpyVzUS5JoaoGWG4ES9mMzwbl8TqmpzAyGRY3DFOpVujq6uJMx/XMeQlm6u3M2RspOHLhOd3fz/ja/0qqamCbgqePP8ToR/+BfDwCvk/G/y6CCimC9MeexRqWk3zEm0V4FRq+3ypZBtgcC3N1IoLjw6cu4rR6KX0IrDAiG7viaEvyHubCMYpq4V6bjjE4KDUPc/01wAOqnCFGfTkgLddRDqw1nfXRTS0PkfDMMnd945tcu3cvnX6RkIghENhag1xkjv5qH5opga8vXA7iEirIMtFq8jQf3Bbin4ZMRNlmMxI8uLrBXLqT2oZdAK0GfNqwpPTz9Ty1w1JvEauUaatXKEd1fE2g20E+897X8YHrUwAkkxLsZ4/UMWwJphphnwJJdBzWNY6AEOixAF12mrjm4+pwphtsQ97TRF4C13m/jqUV+IuXXc0hIcdsoJEnHxxrGXv5QumLhvsw9CKB3hBfSX8HgNfO19DkaeFpUUokyEXjLUbEGvCph1JoBKnNGQihc2VEgu5i3KCgWhOMHt9IUzoU8GRq8hwgopscH/xxAN4d/DZhNd/W67NMT0tzzFLxVkDQ3d1N/eQU/0KDrBBE4gHeeeNafN/nm4dmiSmbhTMKwAYsB91xeE3P3fQWJKha//1vyesCvrpwdidx1/P59rMyXfvyy71lfqBxGYhcJMKJAL4eR6/J2n29UpSLQFJOdunuHy0b0gzdMHj1L/467f2DlHNZvvhHv40ZlAvCWYxIn+wlYTrPEqx+h/GgfHnWellISbp2hRE5d1cebWlELp6aWdGIXDw1U1KpmUjYpC8shZ7jc2cu+h1YpQ+J9bWEqno8QEMxIpkLABE42+Y9qmfRXTkZtUp4MWkvHue3vnCIq9Qi9ehgiMrIMJ01OfmPxjJUA4IONw/AyfQ6Tq0SMK+unvF9n+C6lDzmXAWvamMr47vV+hCAK9sMdS0XZ0TiLS+RAvnO7RgKa1YWjgJKH6IqZgq2HJuGGWBKOcFmskt0vPc93HLbbdx555389E//NO1puWjMW2nmrI0UXbk4puwSJ4e20mtJsfPx24fZv3MduWSadrtA0K8QVqyIxk6KvlxIt0TDGJbsaXKwdDa93izl/cQFRKu+768wIhepmGkCkZGuOPsfkSBsLpGmFpDTWHfQbHkVnZg+SGfgN8iF/pVFkaa6LBe6hq7KkusGa/wN6AF1M5XLbmc5x1qtiGbId2UhNoGPT9JKEjMlwNCNCvdit4DIsc6DfL3PJFCoI3wYDskx6oZiLMeSFHZeedZ1REfku7c8eQJ9WYqZo+UKTkAnr7RCoXoH6zNxpk+dwjRrhGNZ8AXWMZWaC2qcCsjjr2WSwIF/BmS3at2JsjYox8OJPoGutDF6ZR7DrpCudeH5Ht+e/za5qPy7gF3GduW5aL5ACIHhVDCGNqNpdSZ6KzwTPYmOxo/lyrgd8jkWtR4QglIw1gIiTq9PLa16Oi1KQLMu0Uu7v4gvBEtyqiLnDmCX5RyTzlYQvo9ln5vC+7J2BzU/wDp3FMa+D8DY+N/h+xap1HVMTUmg1d3dzZkTM3xapdvu3D1IwND4+U/u5z2f2MeXxhdZjkzzsXV/RUNl/0L1OroVYHhgCIDp/XuJKTQ2WjvbQ+rJsSxLZYtk2OTG9Reecy7HC4/LQOQiIW3eUxjVMrET+wkuzRCyXQq6XHBfTGv3UDTG6371g0SSKRbHRznxmHxBzwIiQzfJf3suLB1nLix31huSK1qQWnHFzOy5saIRuTAj4tXreKqZ4aVTM/J3YiGDwQ7p3zBZuHRqppm+6YutlO5qiQC2nQegO3J+MzBYKeG1TEFEy6G78trLsRhdtRx5IGlXsKdKxBE0vAZHkhonLAdjWQKguWAncymNjC93+m4jwubrrmsd42XbugmZGmeWKhyaLqDHAxidYfChMVrAmZc7MLMrwkKxzsEpeb82quZkl2JEmv1m4uU8y50jhMqqhLcoQVypvCJULTrKiCydZmJR9bHRBanXvx5N07jxxhsJBAJ0qzGQFZ3M2xspunJMDzbmmOjU6VqU5lLPbolyLF8kl2ynvyF3g1rwoPxdfy2nFUt4Z88wqdwxkoVnCdhnC/1ek0kR1zXGahaP5M4VAU7WLZZtB0MgHX3PE7brMbok72Os6HLm5BgAs6oU0xSCdtNoAZGx+Tzmz/wlU+uvBcenkZdj2QuvMCIddg96UP5mNLMeRzcIeg47vSxCAZH52BjxRgAdnbRQVUlGnm9g8/lmp9zEPPg+XkGO7z5DjdFgkuVYkvHufioBCTbNaIyU6qG1NHasdX0B28Y2DJaEfC6u04bv+8wuZ1tsCPl2wspobynRzgnktW5kDGb2wcwB9FgA3Y4yFJBj5ESfoNMtIaKKVSuOEbYThOwonz3xWUx68ISGwCddkqxAwJHj0tTzmMJEdKzlS9p9ANzYuII+3cbplEBk0pNj0/OjNBpRHCsAOoitIXx8tHqM5ekysfhmNiKB82JCLju1znXYNfnfgYZF32wd+7mMCPC9aZfPu6rC6PG/o1abZmbmMwAMDtzD0pL8Tk9PD38508AGtrgNXqvEpLerrtZ/+71TfGHjx6gGi5Tjko0M12osLCww/MrXELIcLMfhZfOSpU09p/fTt1RvmTu2dGFeTsv8QOPy3bxIRBIBXEMuZMKTL3bYcVmuqtz7i9xjJpnp4nUf+B8YgSBLk3I3elZqpmND6z8dX5BVqZltwyt/vtpV9bnRBCKVi4hVm2kZEQ6jxS/ceRdWxKrxoMGafrnQzVgrTeouFK3S3Xg/rmJE3LjAV513+6MXBiKBVYxIQFiY7oq7alc1B77Pgj/EbUqMWM2fwRNCpheUl8ZssINE4RCoWzTQv52gYqBAdrS9Y4uc9Jqi1eD6FAD1k3nsRTnBm11RHjwm79fOgRQRS/75pRiRxCpGZDk2QFhpQequzFeXSodXSnd1OelG4klmVYp706teeU5VTrPfTDGaYcFeT0ExIoO1GWZ7g/QVZcXIs8vPUsiWqEQT9Nfn1b1cooBHnABmQ+7Kb0t38cr9+3nXJz9J6Rv/eNaxorrOG5pOq+cRrTbZkC2xMKELTPC+D3/z1it53+617P/UcWxlFz4fl7+bCRhoQtDb20swGKRerzOr9zJrx0jncuAL9JBLOCLHYLRuEKkmW4xIsnuEqbi8z1vcPJohQcZCfJzOulyYO9QCXdFquMCnil24vk5Mq9DBIuRt2T9GlcAGgmmykQRn6hbu0C557/q2klLeNTnloVGMKPFkrUYxKZ/TkohQKpWo+V4LiNTmEkSVzmqucz1TSi+0YVAxkU9/FC1mojkRhoLy4R/vE4Rq8+htsrtvqCoZrLZqD9l6lq7yOizlvtqtMmdB9Y7o6RyGa1NuW8s3sxKIvGpuD1rAbDEis/UUuoBukYBVglVtxMAKSobl8HenlWBVApGlNtVMMz2Ibq68+2vHqtiqUq0ZRdXo7qPuy+UfHP8GCyc+hOfbpNM3YNtr8TyPcDjMs4s2D3sGOnBzsM42pTe6e1cfG3rAcqC8eCc9xfWk1NwYqtUplUqYu3fTp1pV7Nj/CH+aauPloRV2zvP8lj7kFZd7y/zA4zIQuUiEEyZu4OxFLhYIkZ2XC8iL3ewOoHt4hLv+64rxTn5ulRugEQRVt3/C68FRre637Lq99ZELeYjA8yvfbQpVzUzmklbHqxmRtevlRDBvLNNYvHgJb9NVdTUjUlT27j46veELmwqZzRJeJQqMqiZa5ViMoGsTt6uc8Ndziy6vVZvahwbkLQthSXHrnNnOtYe+ihaVx95+xW3nHOd1ylPkqwdncFyvpROpHlgA10cEdPRUkAcUELl9UwavJK/7kozIKpv35XAnEdXjxwoWsK0CtdpEKzVTVaXMolCkEpLswsZX3HnObzY78M5HO/EwqbtyLK+pz7KYNIhZKXr0fnx8snG5+K2rSpBVsdr4nmqodtOsjuE5rPve79E+Ixe/kjV7zvF+okc+h28sFlh6znjaX7q0PiRgaLxkXQe9TxepNcr4moNhGFQi8t61KbGjruusWSPZtjNnzjA3N0fbslxhw+0WnUEJEuJ1EzsLmtKIzMbWMb5Gar/ChSJCk/dxITbOoBq3cdWV2PVCGHg0/BANIb+zjlNoeYukqFOYV1qiUIpey2TBcuh76Wt5sP0WxtffSkq1oi8HfY6uG2E6o1isagmnWx7jsG8zo6qiUsrIbHnKbwERr6MNH40uFkkl1Abgmc+imw10O8JAwEMHCjHBvL5AMTEkr6Eke860VSWI6S6vbdnAp0qqs64q/9XTeUzb4b5ImLpbp9/uZnt1A46xETejWLlqjO2xCLs6MnhAqSJTFqLboRaR4+D443MEjQ1sUkBkoVvOQ2WjHV0BpnL/CPt3JGn4Z3eubja6s9LDMHwH4GM//RV+jb9gf+QnmZmRx8h0dfM7X5OVOa/FxMsk6AxIwPOvR/6V6fCfAy5OeStbT/wcvqp8S6tnevqzz7Jh+3sAqIwe57pPPEvn1EqKcf9knvlig1jQ4KYNF974/KBjsjTJa7/0Wl7++Zf/yI75YsRlIHKRiMQDeHoMsWrHHo0nqZdtEJB6kTQiz40N19zA1a9+PSA1HyefeHTlL2Nyh3xISBo3USsSSve2/rraclU9j0akmZq5iEYkODLCwIf/nsyv/eolz7OpEYkFDboSPRi+jiNcpk5eXCcyXVrNiMg8fU65IHp6gvQFyj1hVWpG7TrjKr1SViZLmWqOZ70RMq5c0OZElaFwkA4rj8DFQ2PHgWPUuoPourwP/f1bn3sY9mzopC0aYKls8cjp5RYQ8ZUBmdkVoeF6fP+k3CXevjmDq9ioSzIiKjUTtBosV20iKMOyNpfC6GPg+0SVc2tNmTDVZuTOMuV7RAPmOb/ZZESWlJAxrMtx0GMt0RDyHq+z5XUuJuRCPlKTk3623MYhV17XbcseG8sT5B79LJojsHWPcubc422LR9gVj2D7Pp+ZO1u0uv95VMx4ns99//Qsubkqumq81tPTQ09YLmr6Kgy8bp1kafbt24dlWXRkJQsTbrdZY8r7n7YjFBaq6GocFUKdTKoGcscdKEYMakaZaqDIBluagcXUfcFOE2uWrjYkiNhoHUFYHilRo74o75MIJrhBZUq3bu7mw7//Pv7qJ3eTUM62pTB8ac/tzLfLdzRpLiMMEHV4zFli8vhxDKNOJCa1ULkZg6gCRY6qBBnhDEw/DW3DYFfQZh5Cd6OYAtaocXK8q8aZkHwPOnJz4Hu0VeUc0FsephGUYzWgipqE6sFkhHOYbp2v2hI8v9x8CQKBpW3D7VS3ohji+lSUPeu7KIWjLUbEjeawA3kcvYrdcDnzdJl1QYj5JZZS8n2tuwEcQ4LlwvVvpBwzzhGrPj0mx8rVa9rgegkU+qZnKLht3F8bZH5ejvNTfoZjcyXivs9PE8Rav9JcdXp8DD24wNaUBIiPR30CDdXqoiA3F/MzcyRDA7QHe/HxmRInz1odmyZmt2/OEDTOTtn8MCMRSHCmcIbp8jQ15z9/a5R/b1wGIheJcCKAEALTXQEioYTq/dEewgz86AbkpeKKV7ym9d9f/+s/ZfaUMjJLSwBy3JR56W6nctb3Wvbu56maaTqrVi6iEdGTSWI330z81lsveY5NRiQeMtA1nR5DTuLj46cu+J2aU2O5LienvlhfyzVxVtm7e1qC5EUmhlZqRvWbSSIXnkokgicEmWqeCb8HgYZbnMG78Ro2RkP0KDakYqd4x9c+z/QmSX/7xNG04DnHMXWNV+2Qu8wv7Z9GjwUwVpV2G10RHju9TM2WHTu39CSeNyNihkIItfMvLC0QCsgdv9PpUzr5BEHLw3A9fF+jpnqE1HW5QPevWtwrdoWl2hKu59LT1Iig4+PTbkygKlvpbcxSDAnWzu0gqacIO9sAWOvIe1J0M7ixIFk8ki68ohpktCTvs+lqeKfO3tU24+1N0erMcisdZ3s+h1qMyIWBSHGpxvxoEd3U6N4hr7G/v592xYTUvVUUv9KJ5HJyAe/IrTAiI5pcUMJVDbvht6pmfmx4Az92nXSE7cwu8k93JDjSJ7+3yashbKsFRHw3QSMsdQT7l+WCPuxL58+0VkMoozURSnJdSZ7Xou/RlwojhCBwSI73cljwnSuvp5GUc0osLr9nTgjK84tMnj5FMilBgG/14NZ0IqoEOqfJd2lEn5Zdantkvxkxtx/DSCCcANsKOwGpE3EiZZyAT9B2iFbnaKv2ELJjRGupVmpGFbPgqnfGDJZYMhZ4siKrbV7R/TIALEZw2tSHcwY3pmKMbEhTDsQolyQQaQRmEZpHXbEih787TTy2kRGO0gholNTeoYAEf1pM/vu5GpFWx92hNKy/jWqym7Br8Za5b/Ara/uZm5uj4et8dUx+/r/4AZJodPSvlPT/nP0WPjj5bv48v5UMgll89oVUJRGK2Rk2aP+J9fRMyWcz1jhEeIdEW77v802lD3nFj7haJhFIEDHkezFXmbvEp///G5eByEWiZfPurmy3jISceF5sfchzI7xKn+HaFl/64/9FYWEOuuQiMhqQ5z0YOps9qCqx6nmrZpSPyMWAyPMN3/dXUjOqE2x/XO5aJhbGLqgTabIh8UCcZDDZYkRmRB4AYSQJaBcexq1+Mwo0psmBL3tw1MJhMrUc46rjh7vwLNvf/Fo2RkN0N+TOOXsqjh808VLyM0Gj9zxHkXH3FXIy/fazc1Qtp+UnAlIfcr+qlrlts0xjtRiRC/SZOes62uQiXlteIpyUTIWXgsrooZZQ1fF7qFblfSlH5W/2Ble0IfeO3cutn7mVqz5+Fe+4V/bxcISgLqDLPNkq3VxTn+FEn0lsop9YNkM9PARAny3vSdnt5OqRdh5CPs8baj0cLcv74gmfpZHzC07vzqSI6hqnaw0ey0sAcKxSo+b5JAyN9ZFzAV4zUpkIP/ZrV/Pyd21juSAX5/7+fkLq2WdXpXsymQxRZVoXqtUIlyp4gEhDhyGPKxoO6GU0XTmKmik2btsMwNDsNOWwxreu3UY9ci3b/CqabRHEJaQwrxuQoOzoktReDJgTaMIlJWqYNQmStWCCkawEDmeUayyA/6V7AWgEpIjaj8mFJtCmeidNCG476DFfKJBMyTFj5TsIOC4B18UDiqEgkUiEvg075I9aKo0wexAjmKJt7C62luT1nOgTxJwp6oNyDCeKY7TXeukuScCWj8l76Kp7WQ3LDUIgUOO+uGQrr+2+loEhyTRZzhp8Q4ALoSWXa5NRvICG7wWo1+N4lo6vOYTDBerheYQOy9MVnMJVbEQKdJfUMXNOP74HekOO19VVM47rcWAyDyhGRAg+2XMLAPfMfI5d0QBzc3McdHopNjzWBlxep3rZrM2sgPvIlg7uvPHVDLxlC79yi9SmPahK22NK1JujTHhbL8PDG9A8j+z8LAujMo11aLrAdL5GJKDzko2d/ChDCEFvTL5bTVPH/xvjMhC5SIQiJkITGP7KjtuJyMWm7T9Js7tmmIEghtKAtPUPUC3k+cIf/jb1+FpqjsF8WL5A67v7z/rehRrewSofEdvF884PFJ5v1G0PV/1GTIGhwU65s59x53Cz9fN+76weMw2n5aq66OUBMFe5nJ4vTKWZsBX+iulnV850VnPM41PFZ85aont4kE3REL2NRTxbUD3qcnp4PUFlfCXcC+eHrxhIsaY9QtVyue/IfCs9A2B0hVtC1ds3S3alxYgoV1zXrbJ//zs4duy3GJ/4BxYWv025fBzXrRJR6Rknt0yg70q0uryXteUxokof4ogBSpNyp14aHAJk191mlKwSAoHruyw15hDKiKssHDLmKZoSnzW1GU72CPBhw8JOcmpstCmxasnr5Pbr+nhACXz7RquUFNV9ZKjIon7+rqVRQ+f1z3FaXd1xV7uExijREaZvU5J5pUvq6+trWegv2A5Fle8XQrRYkaY+ZDrZwRmjl6Du4qkUm24oobUw0fUIAfWddKnAjjN5PM2g1PHzfKr/LQTdKkJA2lTHMMqkYkeYTA9TI0xQs+iNzpEWNYINBXZCSdqLDknL50xVAhF7dhbvwUdaxmqaW0bvkABEzyhR86Rg9/EQDaG1hKpLJxstfUghmsDTdUZGRtC23q1ugNRHMHsQ04jTNnYXm2sSOIxnQHen8dY1gchpTDfI68VPAjCfbOADlmIWnZAyM9MbfFMxMq9e/2oCfWqcWh1oTgh9GYazc6RMg9O1BoblAoJaUY6XZKKArzlEeuR5zxxa13JYXVSl61lnANfSEJPynq1OzTQb3SVCBhsyMU4U5vj99p8kayToqs1TfvozLDV0jqqKr/c5kxgIqn6DbamV+Tm0IU3itkEiOzt5w8uGWevqLKoOy0ZJ3vuFhQV836f9rlfQpcbkyb0yxf2NQ5KJuHVjhpD5o2fBu6MSGM5WLgOR/ydDaIJw3ET3V3LeZU0u5P/ZGBFYsXl/yTt+hlhbO9npSb76tf1M1xIUYykAhtpXEL1tNbBV+eXFnFV9H+rOxb1ELhWlRrOHBUTUyzyg/FhmzSUao4Xzfu+ZpWeAsytmRFBn0ZILTEgZll0oAk2NiJDHj2hZtFVeIv21PAATboP8FgmM1nsa3Y1FsieiVIwQM729BFWZp129sDBWCMFrV1m+B9cmpbGrgDN4zBbqRAI6N6yT7MZzGZFqbYJs7hGmZz7JqVN/yKFD7+WJvXfxnYe30/D3A+Bl55g1jxFUlL9bL7QYEcvroaLKtwu7pIdMb3Bl7L5j6zvY9/Z9PPBjD/DpV32aPpXuEeYChlgBgmvqM8yqhWJocYhcsp2YUyFoyfN1Y/30DCV4JipYwMOwfbojaxF47NuYJ2edPzUDK06rX1/Mk7WdVf4hz+99mp2dxfM8YrEYyWSS3Co/l33FlbRjE4i0L8uF7UhqLcd9+e7qSgyhmZLVMM00QgjsYJic6lvz1gdPEy18G4A/Xvsz3HfFzThCI0bzPmk01t6LM9jJGSQrMpw4Q8yzCNVVX6Ee+a5tK7gtRiT/2c+heR5xRz4X4ZUJ9Z/CFz5ej7qWpQBesA3DaBCNKn3IaZ+YLUF4RaXyRkZGYORloAehMAl6ABpFvFwDzQsQjc/T4UXwNMFiZBF7nfx+TAlW66ckSJ1sK+BoGq6qWDJJATCvV5gK1AjpIe5Yc4csDU4FAUGwuAZjWbBuaRx8n2PlGlpDAqlCVaWvlbbFTUsmbfqIxkB9CcO3WEzL8ZVz+3EtDW9cPifbzuL78jyfGpfv+JVrZKO7Pzl1nIoR5b4+aUugP/lhnnQG8BHctinD9qkx+Zumx8AqAL46NE3jx5JJCqrxnb20jBCCWq1GuVwmftttrMuWuPb0DFdfeT2+7/OtZrXMi9RbpjcqGZGZyvkB/v8NcRmIXCIiiQBCSMo46Hpkc3IR/c9QMfPcaLqraprO6371g5ihMBNnJvj27AjFeAqA/lULU5MN0XSDQPjc/HzY1Fu75IuV8D6faJbuxgJGq2Nlf0wuDHOBJRpnzgUiD048yEcOfQSAG3tvbAERPRFguSYnqYiqQLhQtFIz1PGBkLGI7qwAkd6qnCzPlGcZeaNsmNc/VWMwP8vysRhn1q8DIXBiqmS2cC5gWx1375KTxvdOLpHDp+3HN5J+4wj3T8jj3DTc0dpVrTAi8rkFAxm2bP5jhobuoavr1STiOzAU4xNSfYICpTLHc59t2bmjQawq72fuSBZLLSZzXfI8+p8zIRuaQSaSYUv7Fjp0lUIxFmm4Kym7NbUZKqEgdVPg+zaVaJz+utwV1r0Yfdv6OV2zcFIBnrLlcxiMbiZVKeNpkPcvPFZ2xiNsj4VpeD6fm8u2KmYuJlRdHVNTUnDY39+PEILZxopt/JOFFSCybt06hBAtoeqx9BqOe3K8xQNyLGoB+XdN992HTyyyqPw2ArUxIoWPc2XjEQzf5VD/Fr66czemrkyurDROUNL8c0jmYWP8JNG6ia5K/UMbpS5rR95ltNrAdxzyn/scAImQPKbmlelon8TuAgLgOjrl9iS5tjSJ5AJCgFPtxqkZxJQZWzURRdM0KcoNxmH4pfKcIu00vK24JRcfj4VNn2BLQGoaxsMV7LWKESkvojs1POXFP5VepK7GpIOBJgKgOTzpSVB7+5rbiZpyvmuyIqHiWvRFQVduDvLjHKvUMRrS+LGkgEg0qjoU24t0rU3guVAdu5n1/imWVLM9yYgI3NOS+fR9F8eRc0FLH7ImzWi1wdeL8j1p33kD/qZX8/HAjzPlpdCEz2/etQlyEgCWEsGLsmsb+5MMCbmh0MslEjH5Ti8sLKAnEvRdeQ0d5Rqle+/j6GyJseUqQUPj1o0X90n6YUVPTD7Dy6mZ/4cjEg8gVDlb1AhQVSrrZt+C/0yx2uY9M7SOV7//VxFCo+6aLUZk9cJUW6UPOV/prRDieQlWn0+sLt1tRlMjMmueC0QOLBzgV7/7q3i+xxs2vIE3bHgDXmnFVbXQkAtgInBxh8Oms6qHg6dBRM+ebWpWzfJegvTkJxi+Wupp/DMF1j0xgePonF4vFxs/Js8/m724sHRdZ4yd/Ulcz+drB2eI7MwQvaqLB45Jiv2lKi3j+z6uooV1VX4ZCLTR0/MG1q/7RbZt/UuuueaL3HLz09y8Zx87drxLXm+5QLj3rQTVIuIHIVLWaBR1cifHQAiE0BjT5HPuC55bwdKMUF0umJZRptxYGRdD9RkQMNVukI3KhX64IgFAyc2wZls7R8o1jBhYy98BoDcyzEBeLQR2Cdu7cF+ZJivyT9NLnKjI71zMUXV1NIFIX18fJcelsqofyFOFlXLLdDrNm3/sx+jMy3FyLD3ICV1O6J2mHEeGqnxpjpGvHJyhEpGLjWFLX56bAwU+Wfs2UbvKfLKdI1cN40UNEo0e7IAcG2VXNq4bSk4SV4UNVjBIcL0EwTvyLjnHZfb+B3AWFtDb2ggnVcmuu0zCLFDfpJyRCwmKfQmy6bZWWsbKSZYtoKzdS/E4/akeQqoknS1S7+PbNfK2HCelrqdoxCfZmpIs3+mkjReHciqMQOpEABp6le7lZepK9Fs15Fg0Qnme9CRQfs26FSG82S//PlQcwlgSxEsVmHySY5U6HYVlopVKq3ImHFsCfEqlElv2SGCcP3MLW/zDrS68JbeTeiNM49QZDEPpRCwpZn56TAKRq9a08RdjU3ho7PT3kZhN8jf3+3z4jAQ8rxyOMlDPoasKMDdzcc1VuifKTjeBpclrHi3Lzy8oT6S2n3wH3b/z26Tf9taWd8gtI52tKsIfdfREFRC5nJr5fzfCiQD1qOze2DYgJ55YOkgg9OIMyovFczvwrr3iam77L+/GMgPUlTnPaiBSvYg+pBnPx0vk+UR5VeluM/qUUr5olCkW8zhqRzNWGOPnH/x56m6dPX17+K3rf0uKO4srrqqlhmp4F7p4B0xdj7SqXCxTIyYKZ9m8B6wKb5x4Gtrlwun7PtVnzhB4tsp0Xx+NUJC6Xidiyns1biWxahe/F03R6hcPSCp1vljnmakCQsCtm+RC5zcaoFquX8oIzjST9A7IVEu8nKdt6NeJGXKBcdM+eqXK0uE4DVXDGkmlmFUl170XoKhd28Moqm69mk2xtOK2O1CfRfgeE50G2bhc/LZU5bWUvE76N6U5Uq5x4+j3aNROU3KKmFqAgeAImppSCo3zp9oAXt+VJqxJp1UfCZa6LgKYVsf0tNIM9fczp9iQqGKBni5WcFeJnocMA9FwcEyNiUQ3pxTg6BSKiQrIczTNFJWGwwNH57FDEiAE64p5CXayJxXl75/4TRLVMvVwCOv6TpzUMLZiRJZKkhHpSGSJWvK3G6EwwUG5wG0ruOieT/ZTnwYg9frX4evymbd5Ywhfx9sgx6S7GKEc6SA2/QQdEQmiChPK9r0kGZ9SPM4aVokmN74cNBNRz+NjIoRNsVvqGzb1DQFwsguoQrFdAoJkUWqJ5uNj3HLYp6GAiKecXa1ggQou0YbJdT0rLsKB/iYjMoS+JKAGTO3lWKVOV3aJZKFAtZpkrLCbUukuhPBwXZeukTDBqIFVjrN5rkYtqOEZDUAjb/fROHWKgDKPtKxlpvM15op1DE2Q6gjz+Xm5aXpr6PtEY/08KQZZJkIQm/e+ZB3148fRlJ9QtO3ioDbdHcEUGlZYznunp2vkvFALiERvvJH0m96EkU6vVMu8SGkZYEWsehmI/L8bkXgAJ3Yl227/Zda96ueB/5z6EDh/B95dd97Flp+U9fdJQye+qtT1YkLVZjwfL5HnE6VVpbvNiAVipINy8pg3l2mcKbBUW+Ld97+bfCPPtvZt/Oktf4qhdi7uqj4zFUsCkbZLABEhxFn9ZsKiQcCRw74Sj+EDEye+xpaf+wkAnIUq9ae/CC6MblZ24bFR0shFYTLYSW6ueu6BVsWrdvSia4KDk3lGlyorbqr9qVYnUFexUWgaWuTSbEDTXTVeKbFYaxCOSudTt8OnNBWmOBGhbsj7FEymsX0fDeg+j4cIwOJkiZh6pFlCFLMrQCTsWWSsLJMZk6xqSb9W9d3x4/0EQgaTx49y5fEnAXhIdREOrb2RpPKkyNXPbhi2OuKGzt1dqdb/P182pFQqUVDtBHp7e1tApDdoEtU1yq7HscqK1qV2UFrRL3bH8ITGgulRFoKYLr+nB1SVipni/qPzWJaHHpa7z3hZphU6/SS0D7PbPsTr9z8sS4ENjdmtg7im1DhNTQXI1pNomk80IgFMNRREtAcRQZ2wC9dPLqI98TgAqTe9CUuo8lFvlrS5G7dXPYwZk7Lezkdf0k0wJcdN9oyFruskS/KeluJxepdj+E2lbiiJv1aWz4e0fYSNhxFqal/b3oHpQCkiyC5pFE1ZSZNQQMSzn2HDrE9NpWY0JCDKKuC9djqMVVlJeTVTM4FqN2Y2gmtplMb2M1m36F5eIlEoAhqPT9yK592Ir4T+xVKezTfKBTV2aj3C9xFh+Q7k/EH8apVAQc5flr3MU4oN2dqb4EMzS7gIdvr72J3ZSMf2a3gifQ0AV3unWT/QQ+P4CYQCIpnOi8/PaVVo4BrKyK1W5HF7DfPzC2d97uR8iVMLZUxdtATmL0Y0GZH5yjyu9x+bh/+zxmUgcomIJKWXiNA7KSzKCfc/W8VMM1pApHK2U2nkimsB6A+dvShVL+Kq2owfVAlvixF5zjkMxGUefTawROX0Mu+9/71Ml6cZiA/wN7f/DRFzZZFquqoS12nY8twv1vCuGS1TM0Vlx5H8uW2aWIEAV//VH7J+u3R6LX3/MPb4I5RiMWbbe/GB2eQZQkrsejreQW6ucu5BVkVnPMhNzY68+6dbTe5eunklx+yVVypmxEXKj5sRTaXxNB3N95hfXiLcvgsApx3mD8rnLq6QvhFCecJ0B00M7fy58rkzBWKqKd48bVjLBiV7VXqmNs10m85iSi48fRV5DaG+dTi2Tc/X/g2Bz0RiHV805X3V2zfTZUrAdDEgAvD2npXn9nyFqs20TCaTIRgMMqs8NXqCJlcpMLNaJ1J6WvZfmmj2QNLnOBWQFTJAq8+MaaZ5xbYe/vqurTTCcsHpKFponk+6EYb2DYQ1m0i9wiueeQx9qiJV10LQGzSZnqswWhgCIJiSu9Z6KMji0iKBQfls3vjMKYTvE929m8DgICVP3rOIt/j/sffmYbKk5XXnL/bcM2tf7r51395X6IZGzdYIjECAkGxrtIE1jMGShQS2B7wI+RlLSAJLY8lYyPLIg60ZDZZsy1qMJCQEAtFs3TTN0nvf/da+5L5ERsT88X0RmVmVVZVZlXWrbt3vPM99uqsql4jIyPhOnPe852X62A/gytZd+xKUtDTTqVE0PaBRHMMtVTk0cRjT9/B0HTM+Rrru4F5tfc9L9juYq/8aNf8+kvwJelPso+aVOF0Q73U+b1FMtBGRwOfsuW/J7RWPMRH/nZEBd6euJFm8eD56H9+u0YjLIZeeUOWeXxTbMbmySEYSbKNZQqN107G0tMTtDwsiUp09y/GVJRxbmFgLMaEs2TOtCbyhUfX0iSF+XwbgvZ1PMjb2On7jC5eo6w4j9UXurTyNbdusPPU0ekwQkektiEhmNIZh6tQtoViNu0XmggyPzrj4fqvUF6oh33VmjEysN8VuNzAWH8PUTJpBk4Xqwp5tx25CEZEtEE+LL0el0GBlRly49qM/BMQgPFgz+A64LO8c1xoXq5ukqoZIRB6RHZpVQ0VkTZ31UFqUMWatRWafOs9Ty08xHBvm4498nJE1JCNURMqJOsggoonE1kQk7Jxx5QKd0vMY8k6tmE7TnGlJnqu/8+8h8Ll0l7jIFmKj2DFBXIqkuJxLsjyzOREBeJssz/zXxy/zhefDNNXWXZUfXrC3KMuE0HSdZiYHwNL8PPET3wVeABa4SR000F8iJua6KfF5HnK6l2UAZl8sRERkJhhGW9FYqLcu4MdqM3i6xvPHRNlhTF4As2du5rP/9f8jtzxPOZZkzhzmOXwW3QqaZvKyoiBDK/XNicg9mQT3pBNowMNDm/tuQrSXZYBIEZl0LO7Pim3/WhsRqT4pFJGn5VwRzVzhQiyJjzQqOkI9sawctqlzDJNabAhPt7A8ODIfg1Idho6DphPzKiQCl+RTK5jP5DGABxNxPD/gSlEQantcKCm1WIwrV67gHBOfhZ07zvm772PoB8VI+yXZNWN7ZVIjp/EtFxoQv9CkiscrR8TiW106BQSkY+LcLabTnB4S71V7YRWAoOlTvjyBG5wkN/lXmPoyhiuOh+vmOevmADjv2ZRSR2iaOnazypzzB9z7nPic6jLd10Zc20p2nqNemqGizcLFC9ExXSqeo5YRaoqTk4qhP0GsXiNTKpKVilW2VmS+2iLBy8vLZMcSHLk1C+i87IVVkrZY6Fft4xStOKYcEeA2WorIhSEDD7g7eIxb7DyZzN286+GT3D/k8vDy38DSPLVSieozz0SKSCzXUve6QTd0chPxKFH2dePiWvBodZrLc6324f8p01TfsMezZQzdYCIprh0HtTyjiMgWCEPNqsVGtADtx44Z6F6aAbhcEwv44TULUxRm1iVVNURyUB6R+nqPCLQ6Z2asRYaraQ4Hk/zb1/xbjmaOrnuN0Ky6Gsa76ylG7I1DsEJEWSIJcXyS+gp6m2HVlTM9qt/8NvWnvoin6zx/SLRkPjVxgowlFsplRlhOG1yZ35qIfPdtEyRsg8srVWquz3Q2xtnJttC5KFW1NyICQE4QqvzCPMaRW5GVBbzRgOStx6lLw3E1KV5zepO7uLlzedKBeHyeFEYdFmrtREQcE1ce3xFfkKmqk+bJPxSdH1//rjcyLks2n5PR+fcuCT/Vam11013RNI3/566T/MVLbuaOPjtmDh2S5LUeKiI2L5VEJFRE/HIZ/7zYtsezQgXQrVVKuSM0NWlIdcT5ZJmyPHiuAJpOJSOO86lZWwyFNG3IHSMVlNA0yOl1zPMlfntqitf58kalJsiBPiXevxqLc/XqVWzpEzkUZPiV9/8L0o88wkLDpayL3zt+glJJhHxZVzRiY3nuuuePOTH6DIGvs/yCOA/DdPliOs2ZM4JY1SUR0UydiZ+6l+EfPEvsVBqd1UgRcWur3CzP/xedgEA3WJ4UqtV93/pLYi4U4inqcfE527JkVLYKvKIhvpuLl85Hn8F3Vp6jlhE/G0OCrM95w4zL7qRcOBzUbfBCvUVElmQb9R2vFN/r45eS5HRxjj2rT/C3v+f/4H2rfwuAlfIqz8wV8RMGj8p4ge/jvzA2+giapnMoF+f7j9WYClbA9/jOX30aa34ZzRT7YGQ3JuAhhiaTUaLsHYkmw6ZLDYt//ecikfrcYpmnZ4uYusZ337p3ZZkQUZbIAe2cUURkC4REpLhUo7Qsrgb73yPSWZqJiMhaRaTYg1k19IjssDQTzZlZY/INSzMvxC4B8K8O/3PuGLuj62uEisiqGc6ZyW4a7x4iKs3EpRxurGA0BLkop5K4cnDW3C/9awBm7r6bqh4nGdT41uEpMnKEe1kT5ZZvtfkQNkLCNjsuYK+9ZaKjM8kv9qeIAFhDQv2pLC+imTZORRzL5nhA7nvfQll2iBTi4jU3UkRKK3VKK3ViBMSR+RaxDIV6S5k4Vm1lFjh+nYy2gh/Ap3//UwSex/PHztIYP8REXSz2fyCn+55YnCTpxbdUREAMqrst1T2FdS1834+GwK1VRCZsk3szSTTgQq3BfN3FnZvHm7RpDgecR3wOmpWnHjtMKZgGLYbhyDlAsn137rz4TJaG5ADAeS1SDRk5TQ7x96QvFLKlfJ1n58W56OjHCQLQck28TEAtFpNEJE0AHK4GrKxWCYKAJ5fnCHTxGXl2lmJJTMQN9IDq3y8Si5VpVMe48Jn/ndJlA90waM4LIljMZDl5ryB7jfMFgqYv900ncdcYTN+DpnmYniChbm2V01LxvJL0qRtV8pJA3CQ/4quTD1AjDGoT14KqvcrDnlA8wsneABfyL1LLCkVESwtSseqmmVgWill8YoJmXBy/ObfVORUSkWN3jOKkKhiug1ETZOnZQH4vK8J79c2rPkEAsbNDeMA92jc5xfOMjb0uer25uTncnPg+fvMvPoUh26EbMQOth9CxockEdfm9DhYX+QGZsfKHT+X51pV81C3zslMj5BJbE5vdxkHPElFEZAuEpRlXlibiGZtYcu/qhZthbddMiI2ISE8ekUgR2WlpRlyU1ioiz6+K2Q5XZWT2yUL3CHWRqiq2YVXWr309Q87aunspmjcjy0xxY6Ej1My9epXyV75C9WuPgqbz/GlxgT0aFGiaOllL3mlZYkF7wfBo9nA8wu4ZEMOy2rEdRSQ+Ii687oq4qCeNHACx22o49z5EWc5WWZQdUhspIrOyVXo0U2JSE+RlMZ6j0tY5EyoiAKfygiQ+vnqMmRdfwHdifPq73kz60gvE/AbT5XnO4VPLWhiBzsuKd7FaX+15v3qB67q89KUv5fTp04yNiTv6mXrLI5IxDc4mxfZ/tVDGPDbF/L+oceVfBDQa4hzWzFWqjRHyzUk0PY0ZaxGResWNTMgXR2TH0VIz+o4wcpoxXRzfhCdUj8srFZ6dFd+1o9kMtRVxnrjHAmpx0YXhGQHmhPg8Ti25zDeafPn8V/ENsViXZU9TFwAAlXBJREFUtCary18DoHkM0GHx8jEu/9WHqC2fxG/OMHnqJpwZ8Rk0Dh3HnkqhpywC16dxsfO7zvTdAJiy1dd186RGAsZXAgJNTBMu6mejh9dNWDj8CHVXdqRZguxOpJeZlB1ES5cuRCMY8uUL1KUiojljaHaKWt1mQioi1vQ0aXmeNszWzcvKygq+76PrGsfuFef+YuEubK3MVVO89t23iOvXt2Zj+AmD4qg4nm/zfwfDSDE09DIAarUaKysruJkRdNNkcfYq1azsIsr0RhqGppI0ZGmmOT/PQ6dHOa4vEQD/4n98KyrLXOvZMhvhoGeJKCKyBWIpi/aIjeF96g+BHkoz2/CItLpmBmNWbe+a+eylz/Kfv/Ofxd/NCh5+12AzoCNVdbm5CojJu7k+FBHXEh+kbc13ZIm4V6+y8Cu/CkD5llczpzto+IwnxGvnTPE1ycq7kpmcwer85p0zIMLLbpvOcHo8xYMnO70s21FEMqOy9VcSkZjs2gimwTp1EyWpiFy1xSK3thQXYlam2E7GzzMREpFYhuZSgLzB5mT1MoYnPrObVy6Qbzj8zbxQr55++HsopbJkLr2AYRjctngegGeHLfIjNSp6dUuzar9wHIdHHnmEH/7hH0aX5t7ZRugREfv5krbyTLV2CV2PUZBTp9FcNKOCe8llVRIRo42IhGpIZizO86OCaIyvum2KyCmmDBmiJ1WkyytVnpkT37Uzowkq87L19bhP3U7h+z6zs7PEpE/kzlWfFyo1vllZINBTQMAx7QqF0hPiPWow9H8ZLDz6EholB03zCZozHL71drIrgqhnbr8DTdNwTuXEU2R5JsLYWTAcrKY4Nk23QG0oz01XxWK/PPQilcTN0cOfPJEgMZkEArQgQNfE4nz78BKJ4UPohkmjWqWwME/V89EaV/DNGpjCr6PnjhIr15lYFoqNNT3F4UlB2PWgRthM7Xle1PF09uVjoDdZdU+SNha4YoqT7iWvEKbVpxaG8E6mCTR4WWyBUzzP6Mir0GU2Thjxnxke5vRLBDnJDwvSlBja3B8SYngqSV2WZpoLC4yPj/NS6xK25vP1i6t860oBXRMl1v2Ag54loojIFtB1jVi6dUHfrx0zAPEupRnXD6IZHGu7ZsJAs03bdwdsVg0VkScXnuQff+4fExCgoeHjs2St0lysRqSjHe2tuwtVsRALRaQHImLL0oycMRI3FjvSVd3Ll6k+8QQYNi/cLPwEZ3mBZk5mPcjnTUo/y+KkwwYz+jpgGjp/9JOv4NM/8/C6GRXbUUSGZQuvkReLfCwtSliFtAMxk8qq+P1FW+zboQ0UkTlJ9ib5BlOyLXkpliVRqbPcEER7xM0zvSQ8GacKM3x69gxNX+PQLbfxl6fvBmB8eY6J3Ai3LAvp/ndo8ML3Vfli5hsDJyJr4QUB821dM0CHYTWVPMMrH/46q6O/DIBmrWLpBt7TcxT9cTQjiemIBdCycowcSvHqHz7Lna8+xPPjglwMleqRj4qR04waqwCk5KC8Z2aLXF4RZZpDaZ3KnFgE3eMBTUN8Vu0+kTtXPb6z8iLnGSama/zoSIPvlRN3CeDobwbEHzNw5AA4ggXAIzU+TaoiyNEtr3wYIBqoWF9LRAwLJm/HlGWRplegZsxxZkGcsEuZF2g4OWaGDTwNnj16lkRG5tkEAZqmUzfL3J6sYQ8fZeRQyyfy9UKFMYTB1DBFTLyRO85QIc/JeTGh15qe5uZpQQrO1Mt4mo5hyBTVZbGvY5O3kJl+TPwOm4IeoAH3HpvA83WeqR3Ckzd8bw1+Vzxn7LujXZyR5vKpqSnueLUo19SlIuLktvaMgRii6EpFxFtZYWxoiITmco/VUgJfemKY0VRvr7fbCEsziojcwEi0EZH96g+BVmmm6TZwG+KuzdI1Xnz4Tr750G2MtpUxvKZLXV7cNivNJAbUvtvuEblQuMBP/uVPUvNqPHToocgnsjApw6C6zJ2JUlUzNrMVcfcVGFkyPSgiUWkG8RpJfTVSRGrxOK7M39BOv4YXHBkrzZOsZqUSoomF6aQ00M45EOtRGdN1rWtqbaSIZHonIhMT4gIfl3kSow/8JEbTohb3uXLxU3hy7spFU+zbdBdFxHN95qWcP9H8IhOaeK3loQmSdZf5Wssn8vLzj4rXuXCBC+UhDF3jlh/9+9QCDctrki0sM+HrERH5+uVV0pY4lwZdmlmLxUYTLxAXsPC8Dg2rTxar1DwfTdN5viAWEt1c5UjsEJqXIMDEclrnjWnmSGYdbn3FNPZxl0tj4jjGmj6uLDkwcpos4rglZckhVEPG0w6a38AN20+PBfi6UMCuXr2KfUx8xrcUPL418xQJSvy8/vPcm/CioX2x4gRJV7yu5ovnutUX0XSduQuyJdh2OHZG+DtiUhFpXCziry0TTt2N7YnvfzMoUqvPcrIuSNel+CX8oM6//j6bD7zTwEu8FCcuPE81eUx8ZxVbB3toilE5PHHx4gW+vLrCKOK7FzMFSdVzxxgurHJ4SRAUa3qaSdkunawUMQM/UrBCn4jjTDF5SmSqPCN9V4dsi1xqlEulQ1SOj4Cu8cqsweHa59A0m5GRh6PdC71CU1NTHL39LmJNj5g874xsb8TBsHTiU6P4mtjnlOtiWRY3azOcHhVE/k13bjxp+1pjMiW++1dLVzecVH49QxGRHpDItO4s92vHDIAVi6PLu4/28oymaYzZVseCWJXx4pqmR22/3RAqIjsNNAsVEV+r8O5Pv5uV+gq3jtzKr7zyVziSEURkcWJjIhKlqrYpIraVw9hiYiu0IrzdQBCvjFZEDyx0KRyXk0m0eIrLZ++hQZOhIM8JLnIpOQ9+PQozG08diiLTv1msbu9AhPuzZs5MLzg0IWRip16jVCrh5EY4fPKdALz4jChx2ak0vmES1zWGu6hFC5eK+M2AWEIja8wy6YgFaykzSqrustjWwvuyC1/lvb/1L1mcE2Wol730BBdTQl0aXZ5DDwKG55Y4WpwjZULV9fnff6eKm7+nJ7PqThD6Q8btVlbKsZjNqGXSCAKelDNsLqzISbhWnolGBk3PAZBKis/Pb1roeougPzv3PHVbYzktjp1TKAlSnzlE3NQwfJeU1qnY3TyZZrVQhDkTGhAkIBkTj7l69SrmaJyGo+METW7K/ykf4OcZ1ZZYbOo8VhHvkyiMYCc9AqBpChnea15h8uQZlr8lsj6WsyMYMkXWGI6JAXR+QOP8miGD03djNcX+e5QAn2lLw2kEVPU6K4lFjMwZFkfTDNeOYZiCiJSkKTNhr4KvYyUzjBwRxGfx0gW+vfwiOj6+5hB3RJaIMXSckfwqo9KfZE1PMzY2xsTERGQqDhfOkIhomsb0hMeweYHL8hSdbOpYVo7Hi/fiS5L/o8knABgefhmm2fqehERkenoab2mJw4t54jKptlciAjA0naIhDav+0hJjY2PoGnzoVaN85Pvv5Adfur5zb68QlmYqzQqFTYZKXq9QRKQHxDPXhyKiadqGnTNrEda+Y+n0poFaoUdkUO27X5z9DJdLlzmcOszHXvsxElYiauGdS68CUH9xdd3zvTZFJBx4l7Q3noTbDkvOo3G9EgGQpoaOiykDl0qpFLE738jTjqjD3699Ax34pjdHqvkiScRF3XEm+Znjk/yfZ49wJrkzyTbKEelHEcmkqdlC7bgs6+SHD/8ommayMveUfD1xZzjt2F2VmNCoOjleR9NgMisu+kvxHDG3yZLb2p7JYBnbc3F9jTGnxP2veojvlMQCPro4Q3pkDOf5F9AJuGtKkNn5ggcEW7bv7hTtGSIhNE1r+UTkVN+ZvFhkdWuV1LyHpovjk07KScL1TrPzC0svArAyLF4nVW+I74quw/Apkn4ZhyYWLWJ+00SapXwep+FhXxTHPJ0W59LCwgKNRgPzdIWLL/0Fbo59Hh2fJ4PX8Nv5aTK6WKQTxSxW0qMaG8Uz0wT4eNoSk2dvxbgsFKfSRGth7PCJPL/aeXCm7sZpyhZzTby+OZni9Iz4//n0Rb7nm+/hf3vql0m4GQjEtcIzhRKQ1VbQm3GMtMOYVERmL11ktii6ZezYEex0CQIPPT7ESM0jLom5OZzGcRze85738KY3vUm8rieOVViaAUhbU9yR+BRXpT9kouTj+/CFxGtB1zjpeYwX/hsAY6Otsky9XmdxUagy09PT1J99jiPLRRKmOP+q3vrrnh8EzLUNRwwxPJWIfCLu/DzjUsnxSsv8wP1HMDYIA9wLxM14lCJ9EMszioj0gLA04yRN4un92TETYqNQs7XopWMG2rpmBpSs+qO3/W3edce7+I1HfoPRuJBlo3RVS1xgmvNVvFLnXWe7R2S1Lu6s0r0SETPcx4CGjDxP6PnIJ9L8rtezPHUfi3oRXdO4m2/jaTbfLF1mpPmceH89hWmm+OHpEf7u1AhjG0Sn9wqv1L8iomsaFRlqNjMnpPBYbIqJ8TfhyjtrX04S3cgfMvuiWIAn0+L5k6Pi4rZoivbXejAaPTZnicVFI+D1U89hjByLItTHluc4cuI0uC56IsE9p1pdQXrsKjWvRrW5M9VoM8yu8YeEWBtstlIQio9mrWKdy6PJTqN0YhUAt0KH1H2xJLwO1VE5QbbmRl4qRk+T1QpoGmSClln55ok080vL2K6HdUHO+xm6hCXntszMzLB06L9Qy75I0Izxb3g/57MfIGEPcdgWC3GymMRIeqzmREZI0yqSmBwne9NtpGUZTzt2qmNfndNiX9b5RMZvwdAqaH6LZBmHxzkj/KXMZ8/TdH2qRXEMPVeqo7qcI+OvYjQT6EmL0aNCEXnK9cn54pzJJY+hJ+KYmijPxFOH0ALQ9ACzfr61fY4g62sVEYCUNsJR54vMGeJvh5o6376wytyQKIf8YHqeQvFJQGN09LXR80J/SCaTIZVKUXz6aeJuk4QcmPf8d77CWvz+3AoPfukpPnJuhrLXIpBDk8ko1Cw0rEJr+N1+w0HOElFEpAeEisjwVLLrXeZ+wkadM2vRS8cMtHJEdmpWDWfNZBMOP3XvT3E8ezz6W6iIXKlewZoUd+hryzOhR0RPW9HAu+wWc2ZC6LqFKcmImxULTMJYRm+IY1XQh3nGFBfZCStJkhp1e4y632DCFwtTSRvt8srbx3YUEYBGRpCvpYXWxfLo0b+HKzNFaglBrrr5Q0AEmQFMWkJBmZwUF/4lLDw0TBLUPdktZAvScd/IVSbiJcgeiRSRsaVZppIylOummzgy0lIKnZh4j91URaIMkTVEpD3YLAgCyiVBRHQzT3ZFx3TkzJ6M9FBUdRFaJnGlJtpktWmhPiTrjY4W3lFtVfzea4XanRiJsby8TMzzsc+L60Ns+BxmU3y2V69e5fiJn8SqjPNH9XfxFe3l3DaeZsp2SBkQ+DrNVfiT5ZtYzYnOEdda5c7v/X4uzcySlmXU9JmTHfsak4ZV92oJv9J2x29YmKOj6G7Lx2QfPczNV8Siv5Br5YIksjary0JdMxCvZzdEIJoeN4XqlUhyceIIE9KoGo8fhVgGWxck3Rg6DoCZ8NCuPtZ6T7vzHFxdXY3UkThpntIO4WuQ9CHja/z2E1dA0zAWqrw8/lkAstl7cJzWgL+QiExPi/N28TtPgRnDkoMtv/Xlv8BfM4/lL5YKVH2ff31+joe+9DT/38wSfhB0hJpdD0TkIGeJKCLSA47cMkwiY3PTS/c26rcXhIbV0AOyEXpJVYWWIrKT9t1606Mh+0LX5ogAHE4LInK5eBn7hOwGWNPGGyoi1USTpi/+f20E/GaIfCIyNTOpr6DLMsRiM88LhrjITlXEQluN5wA4acvMA3ojPb0iUkT6SVYFyIl9Xm0jIun0bRieUJWWLbEgdVNEwiAzTdcYb3wZgNFDJ9E18NBYjaVJNTxWGuJOfixWpjYyxMtHz4NuUoqPcUG2go+tLDBaFou5c9NNmG3lvawpvCzL9WV2C1GGyBpl6o5UHFvTWHSbPFOp4clJyRnbJeYaWDGx2MSGxKLcrBsUlxaj58/6QjZInxDdU6m62xFqNqKL/0+FUadANizdeQHWeXEcYrlLGDWxOF69epVVPo+bmOezcdHpdGs6zhFZ3atUkvzh+Stc9nKs5MQwQ92fY2U1z7PPPku6IL7Lk7fd1LGvRsbBHItDsJ6461PHoph3AOfEac5IIrJozlAz5biKyQRzc4Jsx5uy86SWx/ATaNJoPXLkGJenTjCGICyCiGSxdZEBZOSEamIlPLj05dY26HpERgzDwPd9VldXxXv4No/5Qv051NTR0Ji/IPbzyOyz1MsiW6W9WyY8ltAiIvVnn0UPw8z8GvnlOc5/4/GO5/zmrcf4rduOczRmM9tw+emnL/H6rz3LUwk/UkTqV+ciIrK0tITrri/l7DWUInKDY+xImnf80kPc/vChrR+8x+hZEekhVRXaPSLbV0Ta1ZRuRORQShzXlfoK7jHx98aaC2voEcmH8e5ajBGnd79O1Dkj7+Jtaw5dlmYW9AJNzWc4PcRwRdT2l6Vx75QjFrLL3hCuPzi3er+zZkKYMl213LZ4ApiByMtYkFkp3VJVQ3/IyKEk1qpQRMzxmxhPC+KxGMuSKJaYk50zccPFm4hj6T5kDvF0VYbSlQucPnaM4AXRwuncfBMXlloKgdkQC8xuKiJzXTwiADFD5860+Fw/eWkJzRPHY1KWcjz5mZs5OdG51iIida/Oqi7KB4duFYMiE3WXyookVG3pqqFh9chwnOKK7CTxfYwl0N0YmuGRSojv4JUrV4jHjxBUb2LOEJ/fLck445ogMFcLTdwAppI69dgwmu8Rq13mqaeeormygtMQ73Xszlb+R4iNfCLGsbNRzDtAfOwUOTvL1JI4h+dS5wHITSRxC+I7FfcFgYyVVjFoGdhHjh7jzX/zBW4qCgUkJCKWVET0kIgkPbj8VWgbHBeWZzJSeQ3LM3qtwOO+IFbDiJud07Mu+kKNO6xvUq0K1WZstJWmCp1EJGg2iZ0/jxYXNwmBDOn91mc+3fEcTdN483iOzz9wlp89NU3a0Plmqcrf/c55/u3ffi2XxiepXZklnU4Ti8UIgqCjjLRfMJ06uC28ioj0iP1ekgmx0QTetWiVZrZSRMLSzPYVkdAfkrCNrgawlJ1iyBFEYXFUbLc7W8Eri8XDr3sEksysmuLiHhiZnuLdQ0SG1bi4WlnWTNTCG+LMidtJG+ICdEWmPR6W6/kiI5yr1hkEAs/Dl6PV+1VEYsMytXK5k4iEpZklqRIdiq0nIvkFsfBNTmvQrIHhQO4YE9mYfG6G+OIKVypi0dA1GJcTaskd5amyNKouzXLi7vuoP/us2KabbuI7M63yRtAQF8zd7JyZaXQnItDyifzBBXmM9AqZ+QpoCXxPEwMCZbm1WTMoLgnyeSF/AbQAuxnj8C2341sWOtC4IEsZbS28I6Y4Fg+cGIkCtuJNHw0NqyoW9FRG/H5lZYWU8SrcJ/85ABOWSfXFZzBXhPlzvmLy4GiJu8fE+ZwuXiBVLlCtVqOyzEoiRyK7/lwJiUj9hU7irh2+C8NtGapjsUPYR49yk1RF5tLnAcinLhIGoFqy/BhbzWPqrfcyPYO3fP7T5CzxecZjUhHRzhEEHnosixbLYaV1qOVh8dnW9kkikpbneWhYDSorPCaJSDUhlqHRgof9fIHTuReBgGTyJhKJ49Fr1Wq1iCBMTU3ROH8eo+niZqTKNSGOxQuPfZlKfnX9sdJ1/sHRcR598FbeeWgUQ4Mnjk/wzp/9CL9650tYaXr7ujxzkLNEFBE5YNgo5n0tWmbVrTwiYWnGw9+mIlCodY93b0dYnpnx5jDHBVlonBfbGKohmm2w4q0CMsysHyISKiIxcWF0zEV030bTxN2bicGQfYSkJCIvBmKhyejS8c8Iz/QwY6YX+G0dTf0SkbQ0UfqrnWWPMMxsNiHa/Kbs9V/t+95wnB//19/F/XdJgjByGnSDyYw4JouxHPHlVRbbZs4ckmmiZI/wbdmJMrY8x9EzZ6Nhgc5NN/Gdq4KI/Lsfupd7bxYL+7XwiHQjImHnzFzUMZMnt2oQz4hzLDXk0JTntddWmnluXig82do46ZEE/qggdc1LwpRJYphsTBDpCavGB7Pf5uffdntERByZ42JIIpYYukQqIb5fF772HM+nDTTf47Vf/yz/5ec+yHBcENu6f5SXjsww494GQC7/PElJVEMikh/tnmnhnMyCBs35SvQ9AYRhtdn6fsRih7GPHo18IiEReaL6WQBcXUPTHDS/SWyljCnbYQPf59Af/wl+GsRIGI14/BA4WTStgduQ/pKh41iHRHmQyy3DaEhEkknxmYRE4sXVJiuksTSXF7Qm8xmdLx0yIO9yJic6l9pny0DLH5LL5Ugmk1SeFgPqCmPCz5OYyDF56gy+5/Gdv/5M1+MFMGqbfPimw/zVS85yX6GOZ5j8t5e8jJd96SmemD6Jp2n7koi0Z4kcNCgicsDQu1l161RVaCkiAFV3e+WZKFU1tgkRkYbVy6XLOGt8Ir7sfDAyNss1sTD6Rm9zZkLY4eA7S5zyCX1Z3L3K9saz4ydZvVonJaX5p1xxfGyZPbLMCE+XB9MFEmaIaI6Dbnc3lW6E4TFxx6YXVjtMeSWZ47CcFETFLn6u6/NjSYtkTd6xjooSylRWEL+l9AiW71O1xqPk2JubwrxJ7gjfWBTH/nC1QKYuFj1zcpKiFeeqXPRfcWaUnJMDdk8RqXg+eZkWvLZrBuAlGbHoaZIAa9YqwwWb4UO3ApAdi+MagoA2awbFWUE0QiIy2pzEMHW0aTlnZHY2eu3UyCH0wANNQ5s/h23ozMq/W/KY0BSlxvjIi2SkofrKpcuc0/P84P/4vzj0hT/FiNdJOD5+AAteDF0rc7UhiMjQ6nPES4L0peS54k0f7nosjKSFJSMFOrpnDAtdk5f3ABxnAvvYsUgRWcxeJD1p8eS8CBarmaKM4zTyGKtBRETy/+MP8Z97noZsinLsSXTdwY8JgtX0xPmh545hnRbbz6X1RCQulchQEXlsVbzfmcR5Kk2X/9ss8zelEodzkHXEtWujsszUlPhcZr8jyouNnPjZyNrc/mrhKfnmX316y+Cvm5IxfslI8tF/8/OcvHyBfNPjvzg5Pnn/a/mLfHXfBYeFishSbYm6Nxh1dr9AEZEDhl5zRHpt341ZOmE1ZbtZItGcmR4UkUvFS+IujxYR8aKOGZulMN69x8m7ISzZ6hsuQOnIdGiRMOChRx5m4WKRpFQArmg+juHgu+L9BqqIyC4Nvc+OGYDxkVF8TUf3PSrS+NeoVXFrgiSVk2lSQYGFK/9h4wtpKJ2PCml8IiNKMys5mYiZHqbmic/qZF2YN4PsYZ6VhPKesVEazwp/gHNzqyxzZDhOJmYxFBPHerdi3kN/SMLQSRvrL2HjjsWxmI1eFp+xYRZIV0wSWXHHnh2N02yGOSIGxTlBRM6tngdgQhcXfPOIeLy+0CqD6aOnySC+W6urqywvLlKv17E8D0MmozZdsTDa6XnipiCas9YyE4/+FofmLqLF4jz8zjeKfWlq5PU6ZS9JwZtEIyCbf4F4WRCRpDznnBPHNzweG/lENDkjSQ9EaJt97CiHFyHe1KlTw337szSLgmg3NPEaTn0V3dUwmjG8Upn5XxETqfP3i++nY4tjM68J8hMEorxk5I5h3SbmvrQTkdCsGv43VEQeLwqCdnP6Bcbii2g+aMBtE2FbtEE6fXvH/qw1qhafelpsU0qQbyPrcPahhzFth+Url5h57ukNj1mIoTNT3PPMd/j3v/BBPjKVYcTQKCRS/N/DR/iFF/dXCSTn5IjLrJfZ8uwWj76+oIjIAUO8xxyRXj0imqbteN5ML4pImCUiFJEcAO5sGb/itjJEMjZLtXDOTJahHubMhAhLMw1dLGJZxAU41Rjj+38ox9ChSYqLZZK6ICJzpsGZ7HGacsDeIImIJ+V2o48MkRCjMYdiUrYdL4oSSFmaKXUnhms5jGjLFArfIJ9/rPuLLD4nX0wQkUmZRrmUFMcobloUpL/ARBC3pcQ0Zd1E9zwePHsztXZ/iCzL3Dol7pJDRWS3Yt7DjpnJNWnB7XhJNoleFZ9xjBoaGrop9i87nsB1xbY1awZFGeN+sSy8IIdjQup3Top2WWu1zX8xcoohpFJnWrzwjFjspuLiDr+pa9QbJoYmFu64KUjMlctXMBs15kaneMXPfYTsEXHpvdzQKRhlrjaEEXVkyMX06lFpJiaNpEM3n97weEQ+kbUDIx1JRGQ7tnX0KHoAN82Jn3/zyd8kWZMlKpkhYjfFa5g1naWP/wbewiLWsaMc/ZHvASCVFlkm50WdBicQZRQ9dxzjTpn3sfgMVAUJDRURyxLKVT6fp9ls8lhNkLWbR+aYTLTKIKdkWabbx7qWiOgviK6dlCW23cg6OIkkNz34EADfXGNa7Ybh6TQNO4MRBLy1UuAzd5/k3gvPYDVdvnd448TpvYCmaa3OmQPmE1FE5IChF0XE9z2qkqhspYjAzufNFNcMvOuG9hZeI2Njjsq2xPOFVqpqurM0048iYsvx5q70fmSDGhoezcoQ9foci5dLxPU8uubjo7FkGJzNii+9pieokODFap16W0fAduFLIrIdRWTUtiimcgCRybIs/SHIVuwwhv7ixf/Q/UUWO0szoSKyYIvtMT2PxXrnLJ1vyGF4w6uLnL7rHurPiNdwbrqZp2bE/tw6Jd4/TIDcLUVkdhOjaoj7s0m0sHW3USaeyVIri8tdeiSG2xTb5tUMSqUqge8z0xDKyLG06AKJ3yzIQVgmAYRhVc4e8i2HS+fFwjkVF8ewbhrUq1USMVGmME1Ruqh7Hr5h8q1b7uPOo0cpFkVs++WGTtEsRf6Q6ZPijjdTK3Pzfa8iVxDbeeiOztbddjgnMqCDt1yjudxGlmPi+6F5GgQB9jGxX2fOCVm/2qySkETE0MXna0uSpV8usPSJ/wTAxAc+QE0em3hckLRnfRnyWH+BwG+iOykCRmBYhq5dFiQ4JCIgVJEgCDh/ZZ7nPPHduuOQxWRyLnrMIeezAASBh+e1jnu1WmVFlh+np6fxikWS8+J5SaneGVmxTXfI8swzj36eRm3zcmo8bePK9t/8c1eYyKR5eP4iP/KlPyNVWN30uXuByLB6wFp4FRE5YOjFI1IrlQhNALEe7sp3Om8mLM2kNlk4olCz0hU832uVZ87lOxWRqDTTZ9dMaFb1SgRoGEBcL+BWh6nVZlm4UIzUkKKTwNM0ToUKQWySjGXgBfBiZee12R0pIrZJQaanLklDXUhEmimhSJySYXELi39BpXKu8wUqyyCHBjIi7rJDj8iiFhPTd2o1ZqrtJmaNzy7IdtVGmXg6E3XMOG0dM7dMif3JyQv7bisi3fwhIV6STUJdnB/jpSJHbrmdwqI0II9q+DKLxqvr+D5cnb9AWZZcjg8fByB1i8gSsZoejTC3ZeQMWdnCG1g28/OCDI7o4r3qpkm9XCKXvQcAPfYCY2Min8OPJ4mPTRIz9IiIXHJ1inqFyw3hXzl82yh1GeO//MxVYp5LU9OZOHNiw33VHRP7sDj27T4RzwlLczqsnMMYGkJPp7npcqtkN+qJzzkuA8EsUxAR98+/DK5L8ru+i9SrXkW1KrNGJBH5TlOavutl/LwgKY1LeTgi2p7DPJGQiDQaDYaHBUF99GmhPJ3UrjIxeYbJpDi2aUdjPPZctG2u22qhDdWQoaEh4vF4pMgtjExgNcT+hHNmDt1yG0NT07i1Ks88+nlq5RJf/oPf68iL6YDM5imdu0LT85lt2Nhek5/7L49ybrHc/Tl7hFAROWihZoqIHDCExMKt12huEMoTzZlJpjDMrQ2fkSKyXY+IXDjSm5RmxhPjmLpJ028yX5lvGVbP5fHbiMiiJCKBnmGoD7NqVJpxl/ESkmDoS+CblPMlFi4VScmOmXk5OHA6JhZox5nkbFL8/9MDKM/4he0rImlDp5zOAbC4IO4Iw9JMRZZsjqVGGRl5FRBw6dInOl8gLMtkDoMjpOdJqYhU0amYMbxKhQvlXOs5qXG+kReL+K3pBM2rV0Xnj2WhHTnK8/NSEZkWi1rYir3bHpHNFJGbYza4MmW2UGbyzO1RpHk8Jz5DTTOJB+Kcfv7iNwFI1XOMjuQASI6OUZHnWFEOnmP4ZJQl4ls2qyWxUGUlsW9YBrVKmdGJewFwci8yIQ3GXizJ1PQhGo1F6nVR47/S0PG1gAWGAJ/pm8eoDMs8j8/9TwBWsmNbmppTL58m9+aTUew7gKcLRSHQgKtfR9M07KNHOXO1RUTGPfH4uCbzVRzpyzp/BUyTiQ9+AE3T2oiIKKE+4YpjH9QDvFVBLOrPL8Lhl4gXlp0zIRGp1+uMjIgF/4nzghDcq79AMncnt48+Rdap8vqb5tC1AF2qM41Gi4isTVSd/7Ywqs4ePQuA5hjo8vqiaRq3vUoYXb/1mU/zP3/tI3zhdz/B45/6w67HzpCdaNVLs5iGzj23neUSozy74vOmX/s8f/D1Kxsc9WuPKEtEKSIK+xlOIhEVWOsbZIlUevSHhNhplkhLEdmYOBi6EQWbXS5dxpaKiHulhCvvZPV0yyOCmSXVxai4EWxb3I35fhUvLS70liMuMKWVpjSqite+pAnlZ1ia/WLOJDcnxWI9CJ+IV9q+IqJpGn5Olj7kXXpJKiL5mCAWh2M2R4/8OABXZ34/8kMA68oyAHHbICMv4ovxLPVqlVU3HnXOBIlRzmni7y89eji6G3VOnOCF1QauF5CJmRzKicWs3SOyG50H7R6RjfD88hwEJuAzna+TmxCljXjaQjPE8besHGmZRGsuLnLv8ms4s3A/qWGxeGq6Tk0S0LJsFcVOkE2Iv/tOLCrVJWXoWN00qJfLZHO3E/gGZqxI0pbqSzzJzYcOUSx+BwDHPQSeXKjNCmPmOZzcEM1xWba4JMhRdXzrIMXE3eOkHjqEOdTKxvFYBSDQArj6hNj8Y0dJ1uFB/wTDsWEsWf2IabIsl2y1hQ//8A/jnDyJ51VoNAR5iMeP0fB9vlXX8dBpVg18afJtXCrCkQfEky9/DXyvg4iEish3FoSqeF/8KqnMrQzHVvk3r/k/eNsJQZrDSPd2IrLWH7IgO2bcQ0LVC8syIW575WvRdJ2rzz7FyfuESvPkX/wp9UqFtbAnxfXAnRPfpx972+v5Vz/z4xw5dpxyw+OnP/kE/+j3vrHjeVuDQDiFV3lEtoGPfexjHD9+nFgsxgMPPMBXvrJ+MJHCYKDp+paD73o1qoYI01Ur2zSrFnswq0JbC2/xMmbWwRiOQUCkiHhJKLuCXKXtob5C5gwjhaaJhcvLiQudaYuLW3k5xep8JWrdnTE0HMPBCVpTdwdJRHaiiACYuc501VARWYyJToZpx2Jo6GWkUrfi+1WuXPl/W09e0zETIirPxLKUmw1Ao+ELZajmGyzKaPyHzpxu+UNuvjkqy9w6nYk+j7A04wXerows3yxDpB23HJ5h2Pwm2WQmmrqbGY1HxMyyhkinxGs4cws88OxbeODSm0m3LeaNXNjB9WL0u+ywOH8CywE0kskkhuyEqlsGjUoZw3DwKsKTYch5RUEixU+emIrKMk7pGBlPfGY1s8y08zQYFsa0IB5pGafP0f7H0QdBQN0T54dvNAgkEbHka/3c+Xv4s+/7UxrhQD1NnFOxcEKuZTH6E/9AvpbHqZP/mMOHfwTLyvJCpU4TjaKZxK0YeCtCEXEXGwRjZ8FOQ6ME80+tU0T8QOOFsiAN96WWSSZOomkWnleiVruErseIx8Vxa3QpzYRExJVkODl5XBzjbOc07NTQMCfuuR+A1blZhg8doVGt8ORf/um6Y5U4KhZ3vy0kcCob53ff9SA//cgZdA1+/7HLvPnffiEyZu8VFBHZJj75yU/yvve9jw996EM8/vjj3HXXXbz+9a/fl4ExBwXRvJkNiEg0Z2aLMLMQCXuHpZkeFBHobOEFIp9IiLyc+xJgkLV7I1EhNE2LskSa0uxpmVJRuHonBJCLrwIwb5icyJ6gIcOanNgUZyURGUSWSKSI9DtnRsKR6ap1eeEMPSKzMvL+UMxG0zSOHhWqyKXL/wnfl96WqGPmDO1opatmqUh+V3TFgrFaaxLoBolmg0Nxp80fcia6MN8y1TqXHMMhIXMpdsMnstHk3XacHZ/m5w5l+KHnvij8IUti/7Nja4hITpSRVi+fJwhANzQSmdbddVNOJ25ebA2Ky44f6XiviYkJmrLFt26a1CqiXKM1hdk18F+EwMfXDQqFAoXitwFwFo+QDomIVWE6Jfw88aOdmSHJkxv7QzZCs7lKEIh9DowmzdlnhGFVTtNtXrxIs1QFX5izAznwLv0d8Xlak5PR+WmaaY4ffzc33/RzQKs8WbMzuGUDvzhD4DWgqeGtuHD4PrERl7+yjogsB3EagUGGMqfTHrpuk0y2OoKGh1+B44hSlisVkXK5HM2omZqaIggCkudelI+XGSKZTiICLdPqU5//K+594/cC8Pj//B94zc6SdfqkIH56cRnPa5nRDV3jpx+5if/3XQ8ykXF4caHMW//d3/CfHj2/ZxkjYWlmtjyLH+zcOL9fsOtE5Fd+5Vd417vexTvf+U5uvfVWPv7xj5NIJPjt3/7t3X7rGxZbdc70rYjs1KwqFZHNPCLQ2cILRD4RAM3WWfFl22SfYWYhoiyRZDhLRV7oZkVeQTa2CojW3VO5U1Edv700c77aoOrt7AIQKSLbKM0ApEal+bFcwq3VIkUkH0+hAxOyZDEx/kYcZ5JGY4HZuT8ST95AEQnTVeeTQ7jSBHyuJBbhi3II3ilTELras6JMEbv5Zr4zIz6TW6c6Se1uZYkEQdCTRwTg8lNCeTh86+3kF6RRtYOI5MiMiwt7aUmQ0mTOQWsbQ6BNCNnev9q6AzXHTpOi9d2amJiguRgSEYNmvY7XbOIYohMmMM+h18XifeXKlZYikj9GUhKRulliOifOt9zJ4x37MXKqf0WkWpVpsHK9bDSFYdU+LoiIe+FidN7UjTiapmP5ZSz5XQ28zu/6bN3lL5YESQmJSNMRRITAw8+Lm4fGlSIcDg2rX1lXmlnwxXfvXv05dOnVSqXORu8zPvbdUYdbWJoJ/SEjIyPEYjGaV6/iVCu4hsGYHE65tjQDcOKe+0lkc1TyqziJFMncEKXlJZ754uc7Hpc+Ic4Bu56nsLD+RuPBkyN86r0P89qz4zSaPj/7P77Nu3/nMVYrjXWP3W2MJ8bRNR3Xd1msbmC+vQ6xq0Sk0Wjw2GOP8cgjj7TeUNd55JFHePTRR3fzrW9obNU502uYWYiwNFParkekh/ZdaOucKQrvRrsiYmSctgyRDLk+MkRCRJ0zYey0vgpAIOv0oUdkzjA4nTsdERHHmWTUMhm2DALgucrOyjN+qIhsszQznElTt8U2F5YWIo9IOZlmyrEw5UKq6zaHD/8oAJcu/jaBW4OV8+JF1hIRWZqZHxILr2nZfH1lmj9uvJWPxN8MwN0jQ/iNBo1z4jXsM2darbvTa4iINKwOWhFZcj0a8m503N74fPKaTa48LbwYh2+5PZqzkxuL47rieFlmjvQhkRVSLpW59/VHueXlUx2vox8R56S2tIQvfSDtw+9gDRGR52W9UiaVEpN2jeRljJo4TlevPketJkhCrHAMB0FEDPsysaRYTHPHOqd8W5nNjardUKuFXRXiEt8w03D1CWxZmnFnZijMifPb0wXRtCur0fObCwvRXf/zlRr3fPHbvOtb5yh7XqQKakYaryFzSKRhtXG51NY500lEEokES5r4Tt+nPwtxcY6kU7dE2zo6+hpsORcqLM2sTVRdkv6Qi5OHyNU6O2baYZgmt71SZJs89fnPcM8bxHn81T/6bx2KhjUhFBi7UWTpSvfSy3DS5j/82P387JtuxTI0/uzbc3zPr32Br53fvQnT3WDqJuMJsb0HqTyzq0RkcXERz/OYkHcVISYmJqJY5HbU63UhXbb9U+gfW3pEZF04nu6tNJMM583solkV1pdmzKEYRk5cYPS0FbXuBka2rzkzIaww5l1uR0ZrPz4BjivuiudMgxOZo5FBz3Em0TRtYD4Rb4eKyKhlUpDlpdXZGWry8ywl0kyvmbp7aPrvYhgJSuVnWL703yHwRA0/3bnYhZ0zi7JlOZlIUmzGeOaFJS6PCKXqrtFhGi+8AJ6Hns0yH8uSr7qYusbp8c7wp9AnMmhFZFbGqI9aJra+8eVr8dIF3HqNWDLF2NHjbYpIAleG1FnWEOnjgiyUqj4ve8sJXvI9nWUQZ2pazGHxA9yLwuvByKlo+B3AxPg4TZkY6smZKvVKmezQabxGHN1wSToLaJpGoyFCuBymMZpJzHAasHMRHPF99FKtDJemrrGc738SbK0myLwWCNWoYSRh5gmMkRH0RAKCgPyLItLeNKRPppGncp9UQlwXT5ZDTsUdjsRsqn7AXy4Vebokzn9TdiVpVssn0rhcgsP3I3JSwZaznOr1OpqmMS8Vkfu0Z0EqIsPDr0DTDMbGXodlDUUDKkNFZK0/5Mq3BMGcPXIcPcwY6kJEAG5/teieOff1xzh1/4NYTozFi+e58I3Ho8cYw8MEmo5GQP65jRd3TdP4e684wX97z0McG0lwZbXK3/n3X+Jjf/U83gAnc2+Fg5glsq+6Zj784Q+TzWajf0eOHNn6SQrrMOjSTCLsmtlmaaZXs2rYNbNSX6HUENseqiJGxukMM9tGaSb0iLiSw+SClgxraxV0T/w8bxgcT+QAoSqESkrYwrtTIhIGmm1XERlpyxKZfUF6PgyDmhPnUKyzXGFZWaamfgCAi1d/R/xy7KZ10ZVRuqoMNcvI1mWABdlOeksy1pq426aGnB5P4awhhruliMxKn9Jm/hCAiROnePdv/mfe+k9+Ft+D0kq7R0QqIlaO9Ik7ASg3LfzFF9a9TiKbpSzJXf2czGTJHSMrSzO6rjFs2yBb5bXQ3FoukxlJUFs+Lt43Pst73vkObrtNlgWbIvhLqwnSodlz4IhjX6lWaciOsLJjMXe+ZZTtFSERMQLxObpmHK4+gaZpWDLYrHBJEKt0U5wLjpun8HYPPyU+y6b08WmaxpvHcwD897llLkgTrVUX5NVIx6LOGfdKicDJwT95EX7qcRx5njYaDS4vlyl4Jjo+d+kvRIpIKnUzL3/Z57jt1l8B2sIHNyAi33rolfz8O/4BF9/wRry8nEO1AREZnj7MobO3EgQ+L3ztS9zx2tcD8NU//u/RYzTDIMiIbSm+eHnLY3vH4Sx//A9fwVvunsbzAz7yZ8/wo7/9ZeYLg0le3goHMUtkV4nI6OgohmFE0ylDzM3NMTk5ue7xH/zgB8nn89G/S5cu7ebmHVhsVZoJiUiiX0Vkh2bVTGzzxSNlp6IF7EpJXEiTD05hZB0Sd4x2lGaGtqOI2CEREdsz7DcIi+gjGaEqrOo6WHFyhvh9qIYAkSKy0yyRMNCs38m7IUYtM0pXnX1e+DX8VAY0bZ0iAnD0yDsBneXG05QSxrqyDLTSVZcNsTCmNAMnkaQSS1BOivPkbDJGra1j5qm2jpm12D1FRCz4E1sQEYBkbohDZ2+lsFSFAEzHIJ62OsyqidwwuhYQoFF6YX0kfjyTpSzP28aLkogYJjlZRhnNJEAmfhrZLI787tXLZVJDMarLQmFJjtcYmZ6OjKqx4nHqfgBVGQ1vLUeKSHF5kYr0+ZQdm/kXn+/vINFGRGTpp2E4MPNER8JqcV6o0smaIPWxcR0/B4H0WzTbGgq+VxKRzyyJc3fUMtFkUq2VjeEXZwm8BkHDo7lYhYT4rrUnq371RaEwntRmSGp1iA9Hf4vFpjAMWSJqK82USqVIGQ9LMzfddIpj3/c2bn/oIfyy+C6bXTwiIW5/9XeTyOYwbZv73vgWNF3n4jefYO5ci3gaIzJL5HJvM1zSMYv/8+/czUe+/07ilsHfPL/EXz93bTwbBzFLZFeJiG3b3HffffzlX/5l9Dvf9/nLv/xLXvayl617vOM4ZDKZjn8K/SOe2rw0UwlLM32aVUvbaN9ten40tXer0gx0Rr0DOEczTH3wpcRvH932wLsQUagZ4i7KJsCWSZLT48JDMG8YnMiewJVlGsdpeQYGUZoJgqCliGyXiLQrIs8LYlCXZGGtIgIihGp8TNwJXnz1W+DBf7DuMWH7bkl38NBJNFyGpg+xMCxuGI7FbJKm0ZmoumbGTDuiULMBT+CdkaWZrRSRdoRlmexYHE3T2ohIFk3XSSdkaNmFb697biKTpSTJXaOthff0eJIcee6dMiN/iDE2ip2QpZlqmXjaor4qiEhqqolhWhQlEbEXDrPUDHCa4vElwwc50ba0vEQlVCEdi9W5mS2HWK5FVRIRU88B0LRsqOWFYVX6RIqSQCFbm61TsiQ0JM6FdiJyZyrO0ZhNXXorziZjuEVRdrGGbCDAL8iE1cut645pmuiyhPa1C0LRvEOXhE4qImsREZHGMleuiNccHR2NSM3Lcil+/qbDfJ881pqlo8U3vrbc8opX8r/9u/+b+77nrWTGxrn5Zd8ltueP/lvrPaVPpDEzT9BjmUXTNH7g/iP80T98BT/1mtO8/d6t814GgYPYwrvrpZn3ve99/NZv/Raf+MQneOqpp3jPe95DuVzmne98526/9Q2LSBHpEmgWBAHVQp9EZAcekfZBecleiEiYJVJaL5F2lmb6JyJ2aFZtrtKwBVmzEkLeHB8SF8/5Lh0zIUIicqnWoNzcXpkqqNcJpIy/XUVkxGoRkfAzLiZaYWbdcPTo3wNgtvQl6sNT6/4+lLCwZYBb2UwSK1YYnjrEwogoy9yWEotT/ZmwY6YV7d6ViMiumdXaav87uAlmewgzW4t2IgJEpRlTng/prPgcilfXl2bimSxlSXrq51tx+cNTR/lpfpsHM3MRETFHx4iFHpFyGU3TCKpCfbAzJer1OarV8wBYV6dZagbEmmLxzxt6VJopLS9yYTRL46bTFE4LIjN3rj9VJFREbFOWOcJS29UnsI8JIlIuhsP7hDJhJaQJdUicS26bkt1engE4m4rhrgpSaOekYXVJEDX3cqnjeSGBePyieL/7dFlO3ICIhDcM4HP1qnhsWJZpR3tZZrNMIcO0OhKk73/z9wFiFk1BhgLGDovvuVldobjc343G6fEU7/vum/vKNdoJFBHZBv7O3/k7fPSjH+Vnf/Znufvuu3niiSf40z/903UGVoXBYbPSTL1SxvcEoei1a2YnHpGiXDgcU48Wus2w1rDajo7Juz1E069FaFZ13RXcpLhAawlhshtJi0V11jA4lT1FrSa+5E4bERm2zKhT45ltds6Eagiahi4XrX4xapsUU52f3XJcLB7TGygF2ey9ZDP3EAQNLl/5z+v+rmkaE7KFt2QkcZZXuPXh15KfPg6Ihae5skJzQcxWqR85wcVloSLdcg0Vkdl6bx6RdoQtmdnRkIisAsIjApAeFdeisFTRDqGItEozUbeFnNPD4rNRhog5OooTKiLhTYAXxy0Po2kBV67+FwAcawqzkWbRbykieb1FRIrLS6yk4mg/9RNkbxOt5XN9lGeazRJNOUU3ZovztxkS95lW50xN5lB4MaEGGI74Dhij4txqrsl6evNYLvr/k3EHd0V8/nY2QIvF8MKE1SudN0CO4+AGOs/Oi3yVl+qi66Vhdp9uq+s2pim2YWFBkJvuRKQ1+qEfTJw4xdHb7yLwfR7/1P8AwBoXx8CpF1iZXZ++up+gSjPbxE/+5E9y4cIF6vU6X/7yl3nggQeuxdvesIhtUpoJ/SFWLI65xfyKEDvxiPSaIRJibZZIO5arO1NEQo9Io7FMkBIXnvmJv+Kt77uHjCMWzLWKiBPr9DL98PQIP31sgpFtmGWhzR+SSqFt0vWxGZKGQSMz3PG7xbYws41w9Oj/CkA+//Wuf5+QvoeSmcSem+foHXfh3SnSKW9NxqNEVevIEZ4rClI6lY0xlFz/nrs1+G5WttD24hEJkQ+H3Y3FCQKPZlOGdoWKiCRbxXwBmp3ZELFUmopjESBIpCe7Yxi/TW7QkzQXBTkzR0dxQkWkKue8BMXIJ3L16v8HQFK/iYYfUGgGxFzx+FXdiDwiJfkeqZERxk8KwtMPEQnVENPMYceE96EpfVFcfQLr2DE8TaMpy5tNSxAxww5LTIKkN+VAvxB3peOE37pC08NdFueyHW9gjo5GLbzu1RKB1ypvOI7DUpDEC0R31kmECrlS31hBCMszK7IbpxsRaW5hVN0ML5GqyJN/+efUyiXM8bCFN8/K7P4adLcWoSJSdIsUGxsPN72esK+6ZhQGg826ZvpNVYVWSaW8DY9Ir627IUJFJMwSCeH5XnR3vd323bA002yuoqXFl9l2l5g+k4OCeL850+zIEGkvzQD8kxNTfODkFMfi/V/8gB37Q0I4Q0MEtC7k5USauK5tauIdG3sd997z/3DP3f+p69+HbHGHXCOOXq7gFgqRH+bWVLxnfwjs3uC7XibvrkWhrTTjunlCg7Il77pTU4IoFBsWLHUu+IZpYqczkWcjinqfuA00HcoLNGdku/nYWJsiIhYzt7ZETRKR8JyKu6dYkgv1hCZLa4ZO0xbPLcrE3NTQCJMnRQJuP6WZMEMkHjuEJQ2hTV0qeDPfwBwdpZ6W/ooA0Bx0zUO3BdG3psSivFYRWW16hFeAbxTKNGXAmWlXMEdHCUrzYAQErk9zoaUqOI7Tats9ksaULb2L5Y2DAaPOGXcZTdO6NjdEpZlc/9/FY3fdy+jR47i1Kt/49Kcw5YRkp5FnZWZ/E5GElSDriHP3oJRnFBE5gAiJiCjDdJKHflt3YWdD73pt3Q0RhZqVruD5rW3PN/JRpLGvp3cUaBYEHlpWXGyHmy5lt4ybF62MK1aMQ6lD1GutMLNBIsoQ2SERGYnFKCVbr1FKpqNo942gaQZDQw9u+JisLge3GWKRev7KLDU/IK5rHIvbbYmqbUSkS8cMtBSRQqOA63efAt0v6r7PsjQ+b5WqGsL3g0gRaY93N4wUui5eIy2TaotNB+a/s+41hE8kNKxKn4idgFER4e5dFeeOOdZZmgmCgFpphqps4Q0RKx5nqSmIyEmtNfa+aJg0XTf6jqZHRhk/Kdp883OzPRtWq2FgWmwaOyXOed+o4OtpqK2irV7AfvObxINNC03TSDgNfDkBz5Lqw1oi0m7S/uxykZphoukBplHEHBsFAvSYIAfthtUOIjIprgNNDBZXN96fMEvEsuqMjY1hd1Fvo9LMJh0zG0HTNO5/09sA+Pqn/hBtWBwnu15geWZ/l2bg4GWJKCJyABEGmsF6w2q/qarQmjVTdb2+g3v6VUTGE+OYuonru8xXWhfCqGNGT4FmkN2GR0TXbQxDHJsgLe4UxzxP3LUXxF2kNXQMDZ96Y33XDAizb3NhgcDfXsy7v8M5MyHaO2dAKCIb+UN6RbIp7gQrtiAX314UasbNyTiGprWG3d10M0/Nrp8x046snUWTik2+nt/RdoUIo92dLZSfdpRX6/jNAN3QSA3HcJthhkjLKJmWrZtF14GFp9e9RrthtXGuZVhl6i4AmtLwuLY0Uy3kadaWqK0cIwha5M9eOMxiU5w/R6xvk5Ln0qquUV4R57lhWcRSaeKpNNlxUTrptTwTlmZisUNY4QBCs4w/8hLxgKtfx3z1KwHh3QJIJvQWEZmURGRxsSPqPWxbj+ka1QC+fPvdmAkPrZ6PFAUQn3WjzbBq2U4U7X7fqHi9KjGWVzZWy8LSjGXXupZlALyCVES6zJnpBWcfepjU8Ajl1RXOnROE0G4UWJkp7tksmV5x0LJEFBE5gNANAzsu3Phr76IiRSTdhyLSRiLCVtxe0Yp3722RNHQjCjZr94lERlUji61pxPXtOdTtMEskJjpgxpoeK+UZ7LogCJnRszQaC0CAppnRBREECXnu4Yd57rsexr26vQvAoBSR9nRVEKmqm/lDekFCEoaSJCJPlYSScGsqRuB51J8XC6Fx+gxPz8po9w2IiKEbkXw8qM6ZKEPEtnruUAg7ZtIjMXRdW2dUFX8TRKTi2TRn1isiiUyGUiwMNWsLFwuJiLyzNzrMqmVWZmcI/AJBM0ajIM5p2x6nORMjL79Gh+xvk5Wzi/IaFOVE5fTwaLSPE32WZyIiEj+MZYnPwLPKeLl7xANmnqC0LL5PMUMQukTSwTOl+XT8MOg6+H6UGAstInKLDPb73L0PYCU8aFYxpKIQSCWx3bCa92zqmNg63JoWv68QY6nttdciDB+0rVqUH7IWW4WZbQXDtLj3jW8B4Guf+wthIMfHz69SLQ5GxdstRIZVVZpR2M/YqHOmWgxLM717RBxTJ1z3+23hDRWRXs2q0NbCW2wRkcioKufMbLdVLuqckQvLqOdRWRaLS1XTmB65tW3GzASa1vqKaJqGOSQNr22ZEv1gp3NmQoy0dc4EmkYlntyxImIVxZ19wRJ3r36pxIhlcmsqjnvpEkG1iuY4XE4M02j6JG2Do8OJDV8v5+SAwXXOzPQwdXctCmtad5tdiEg8ncGUClvp8rPrXqNTETnf+sPUnQQ+eBUZqtXhESmxOnuVwBcLb3XpOADp1G3My/bQTBaSxgo5qYjk8SKCkBppEeCJPg2roUckFpvGNMX33Dcr+Gk5XO5qGxGR5al4MokfEhEnhzkqTa5thtWnJTF97Yg4dx+9/V68rCAyZlbsty/Npe5MiUCqPpdq4j2OZTQs6RmqEmN5eeM5LeH31LK6KyJB08cvifNhO6WZEHe+9vXY8TjLM1dAXhOd+v73iUQtvKo0o7CfEXXOlDuJSMus2rsiomnatgffFXsceNeObi28LUUks60wsxBRqJkpiMyY59GQg+DmDYNTQ6ep1Tf2h9gnxZC0+jaJyE7nzIQYtUwK6RwAzXiSQDd2rIgYK+KitqrH8NH4+99+jG+/4nbeeWiUWmhUPX2ap2Ub5i1TGfRNlKkoS2RAnTO9Tt1tRzjsLjsmCFN7qmoITdNIy4W/OPEQrJHl21t43cuX8eviTpzJO2jW5CXUMESyqizN1CplVudmgCaG2WT1xe/CMqeYTL418occmpIkSZY/VoMGxZCIDHUjIi0/yWaIhurFDmFKRcS3qjQdOcV35hvkZfaJpovzMBaP4ZuCIBlmOuoiCX0iQRBEHpHXj2SYqpapxWJ8+VbRVWXKZN7m/HkRLtYMcOfEsT9XFMfoeMqHakhE4lQqFarV9dNuAZqe+Lwsu9bdqFpsCM+xoaEnt0/AnUSSOx/5W2Kb5EfpNPIsXy9ERCkiCvsZG3XObMesCi3DaqXPLJHII7IdRaStNBOFmelZctvwh4RozZsRd2uJIEBbEhf4qHV3E6Oqc1J0QESmxT4Rds3oO1RERm2T1bRYTEuSkBzuEu/eK4IgwJ+/BEFAE52CnaQpA606/CE33xwZVTfyh4SIFJEBdc7MbIuIdA8za1dEANJjMkvk5FvWzeGJp7M0TAPPtiAIaJwXd/3EsjRtsbibuTSarkeKSKNSYXVWZtEkoLZ8kiO5PyBbf5DFkIgMC7UhGyoiXiNSKsJyEcDECUFE8vNzVDdISw7hefVoWGM8dgjLbJ1nrhYHw4baKqtzonzjIaPYDVe20IBprCci840mK00PHTiTjPOac+J8+PQtIqXUTEkT6uIi9mFxE9S4Irb1hbz0w8QaIJVNV2aIbFSeya+K58TjLpa1/vPuNcysF9z7t74X3TAoNsX5ZTdUlsi1hiIiBxQblWa2Y1YFSMgskX47Z0py8ehHEQmzRNpbeFuTdzPb6pgJYdkyXdUvUTfFwm3OPAnAgmlzOHV4w9ZdAPuEUES2W5oJc0SMHSoiI5bJ+SOnee7BR/jsy8Ud3fQWs3w2Q7VYwK9XSMjBf4vxDO58K1mz1bp7ppWoukHHTIhQERkUEdlJqmpmbG2YWWeqZ3pEds4srZ8XksiIOT71tFxg2wyrzdhxoLUQR6WZaoWVGXH+poZkPstyjcpMmbxs3Z1OCUITEpHVRoGSfP/UcEsRiaVSZCfEuTj/4vr013bU66IsYxgJTDOHrjvogfBQNKoFGL8V19cpzIsFzNUE4bA0sfBqgY1hOJjj4niERCT0h5xMOMQMnVc+/iUAPnvoXqq6jZmUmSRLS1jTMpn1comVcoOrJbF/U3YdqqvifeQsmo3KM0tLcrCe1T04cCcdM2uRHhnl7EOvpCavK059/2eJhGbVheoCrre//Sy9QBGRA4qN5s204t37m+OzbUWkz0AzaJs3s4FZdSelmVARabjLVGOCjI2uiPbLRnIEQzeo1eWdbGy9Sc6Wikj93N4rIoFu8Of3vYbnJ0SMeLeBd70ijLpOIy78S7EszdkWEQlbd3vJEAkRKiKDKs30myESBMGWqaohos6Zpc4QL2iph2WZHdNoM6x6howGd8R5HhIRgiBSRLLj4rtYXK4x80KeAEglTdK+OO9y0qxaaBSiDJH0cEsRgZZhdXaL8ky1rWMmVAoMTZxrbm0Fpu/ma0uHcWsNDBMamlBbTJlnYupiWyNFZCEkIuI43pyMEQQBZx77ChNLC1TMGJ8ZfgAzJstZros5JN63caXE1y8JEprRqpheLSrN6CmxfxspIjOSCGhaFd9vrPv7To2qa3H/m7+PugwptOrz+94jMhIbwTEcAgJmK70N6tvPUETkgKJbaUbMmdmeIhKmq/btEemzfReIumaWa8uUXXFBaDerDu1EEWmPeZd3ZSfqYvHVMuJ965t4RJzjxwHwlpbwVlf7fn9vQIFmo/KiWZGL2LBlkDC2/3XOS/Vj2JJhU/Ec3vIyfqOBX6ngXhR+ncKhEyyVG+ga3Dy5+T4Mx8TxHZRZda7RX2mmVnJp1DzQIDMmPAxRacbMdTx2M0UkJCJF2eraTkKbviBjhiE+V9O2MS3ZYVMR5+7ItDgOpeUac1fF93HycApK4pjnZF7Oan2VklQI2s2qIGLJgS0n8ba37oYwjZCI5Ckkb+IrS4Lonxyt4mnSixHI+TvSMxJGnrtrFJGzyRjeygrUarzy8S8D8Edjr0bzyhi5HACaLUiLO1vm8RfE/kzoJer1OlTEz3ZWlMK6KSJBEHD1ymrU8txw1z9m0ERk7OhxUsfFTYZdu0w536Be3d608WsBTdMOlGFVEZEDijBLpF0Rces1mq64u9i+R6Tf0kz/RCRlp6JkzrBzptOsun2PSCjJu41l/KRYfMJXSwyLu8PQI9KtNKMnk5iynXA7qkikiOw00MzuPAaHdqCGABQWxKI4GheXhKWkTKGdXxBtu0GAMTrKMzVBAk+OpYhtQQgjRWQA7btBEESlmV4VkbAsk8o5mHJb3abYlg0VkcX1ikhI2lelh6LdH9RsyPKetgo1oRTZiVYnUWpouE0RqTMvB8UdOjMUEZGMJJOrtVVKMkekvTQDbYbVLVp4a9WWUTVEmCDrunk+/9UrNAODyUSJW5OCFDkxDd+TKanSU9LyiIjj8XQpJCJx3Cui/POac0Il+/ORl1GthqFmEFSXGfnhW5h8//18VSoiY5okIlIRiQ8Lj0M3RSSfz1OpVHFdSR4b6x8TEhGzzzkzm+HYK18NgFNfJvCr+14VCcszB8GwqojIAUU3j0iohhiWheXE+nq9xDZj3rdjVoW28kzxMkEQtE3eze7IIxLmiDTcFbRMZ+klN34rQeC1hZl1T1V1TmzfsDooRcTRddJtCshO/CHQUkQmZffD8pC4Y23Oz0X+kNhNZ3ouy0CbR2QAiogXwE8dm+BHp0cY79EjEvlDZFkGti7NuGFHTBtC0l6S5K/x4otR4FVzVSxWZsyD2W8C4LQFCuYmp0kPi2O6OldhpSFIx+F7xtoUEfG7leoyge+j6TrJXKeHpcOwWixsuM+t1t02RcSWA+QWL/P0408CAY+MP4sdiO1KDsVoNqWiY4nPtd2s6gdBNOTxbDKGOyPe406/wSG/TMVI8FeNGIZs+fWWlojfPkqQtfnGFXHNGQ8VEalsJkbE93tpaWldeNhVmdETBNKT05WIhB6RwSgiAFP3icA3x23i1b+x730ioWH1IISaKSJyQNGtNFNp65jp12metLc3+C7yiPSZcdHeOVN2y9Q9sUD4emZbc2ZCRIqIu4yVOdzxt6nJe2k0lgiCJqBj22NdXqHVwtvuFegVg1JEQPhEQgxKEZkeERf/5aScUTI7S609UXWmt44ZGKwiYuoaP3N8kl+++QjxHktQhcXOjhlo75rpXOiHDx/hp/7T7/Pjv/Zb69/bsrDjcSq2BbqOX6lESkFTtsGacR9mhek5FvpEgNzkFKlhsVjWyi4BEDc0cuMm1MT3MTKrSlNvMjeErnee47FUityEIM5z5zY2rIalmXi7IuJkCQJ46nnxvNunXCbiZUreiHy/GF4grhOWJC0hEfGWlpiT/hBb0zgRd6IwP3t6mjdpQj38I28UU0blh9OIn5opUHN9MjGTrFbrUETS46LbqF6vU6l0dqiERMQ0Zav9JorIIIlINIG32STwvkE8tb+XR1WaUdj36JYjEt5JJfpIVQ3RyhHpTxEp7lARuVS8FJVlND0GurPDHBGxwHpeGTvXIiJNYGri7jZ/yDi63n2bI8PqC/0RkcD38eUwtJ0qIgCjbW2NO80QyUtT4tEJcfFfkCPp3bn5zmF3PXbMQNvguwF5RPpF1Lo7LoiI51XxfbGArVVEdN3YVCWMZ7L4uoY+KZSikIRGk3djPsx8A+gszeQmpkikbXSzRfzHMxaU5fgCzWiZVV3xXV1rVI2e10OwWTePiOXkWHk2S6FYxY7FecXLhfG17IvvQjJp4cl4d1Om4Rq5HMjza7SY5/nvuoMvPXgLpq5FRMSanuZ7LXE+/LkxTXNMqiiSnH3tvPjc7zmSRdPA85oEkohYmXEy0jC/tjwTEpGYI4hNw+38e+AFIkeEwRKRMMRND8CoFijMPzGw194NHKQsEUVEDihCRaTapohst2MGtqeI+H6wLY8IdHbOhGUZDHGRzFnb94iYZgZNE/tipFt1+LzlYJh2q2NmzYyZdjihItJnC69fKkVhWYNQREbsFiE7tINUVdFdIhbGE4fFYrKoyyTSuTnqzwgvgHfyNOcWBZHqpTQTDr6rNqtUm92Dq3YT+fnO0kyohmiaGc0c6hUheQ/kXXMYaOfJu38z5kVEZG1pRtM1UkMtkjMxkYCi7Eiyk2SlWbXm1/G0YJ1RNcTkFsFmvu9GYXztRETzk1z9iljU73/tW0meFCFkZamIxONmlKpqWuK81HQ98nw05+bQNY1pSXabM+I7Yk1Pc29c51BtjrJm8+UjgqCHROSxi+J4339CvI9DA82X14/4ECNyP9sNq0EQREQknRalh7UeEa8kw8x0DT21s5JkOzTLwhgW5OzQ1GEycsbPfsVBinlXROSAIprAWypFA9q2myEC2/OIlNtISz/tu9A2hbd4JcoQ8XSx+O2kNKNpWqs8E2vdTZXj4phsZlQNEWWJXL6M31jfWrgRwrKMZtvozs7v5AaliFTyqzQbddA0Th4VBKyEQdWwqX3rW6I7SNe5kBonCGA05TCW3nr7U1YKU6pKgxp81w/ya0oz7f6QfkuTIXlvjkiP0bnz+OUyviwrmDEfFp4Bt7quNAOQHm4dr6mTmcgfgumQ9gN0OSCwbnvrjKohWgmr3Usz9foc4KNpNrbdUlWe++sZmhWLWELjjrtfC9N3Ay1FJOEY+KY4VpbZIpjWWGfnTIjQrGpNTaPFs7xp8XMA/PmI+M6EKtHjFyQROTaMZVnEZWs4ZhyseERE2hWRlZUVarUahmGQzYo8obWlmagsk7HRtjlzaiOEJanX/e0f4fid9wz0tQeNyKxamokmk1+vUETkgCLsmgkCn3pVXCy3m6oK21NEQjXE1LVoymeviELNSldYqIoLmxsSkR2YVaGthbftdbyUuPuJSjOxjYmIOT6GnkyC5+FevNjz+3pRhkj/ilQ3tHtEdjJnJjSqpodHyaXi0We9FM9S+frXAbCPH+epJbGQ9FKWAUH6ovLMgELNekWj1qRaECRxfarq0IbP2wjhd6aRFQS/8eKL0UA4LRFHz41C4MHcdzDbRtaHvo60VERiGgwdayMiuoUOZHTZ8mv5G5dmZAtvYaG7YbVVlpmKZiTl52d59q+FgnL8Tg2tBozfCrpFyRPfg7iptUozbUTEnAgNy52dRFFp5tA0xLK8eeGzAHzWStAwLZoLC1xdrTKTr2HoGncdyeI4TouIxMXxH5bqQzsRCdWQiYkJYrHupZnd8IeECKcIh0rXfsZkYhINjYbfaKnG1ykUETmgMG0bU951h4bVnSgi25k1094x0+8d6HhiHFM3cX2Xp5fFaHbfEBfJnXhEoG3ejFbHlabAxLC4yG82ZyaEpmnbmjnjR6mq/ZUFNsKILFEZmphIu12ERtWMvAOezIpFczGWBTkHpZ8gs3aE5Zlr7ROpFhsksjaxpIWTkHNimuL8X5sh0gvC70wlIUhN49y5llF1dCyaxMvME/jymBmWjSP9IqFPZdTUsMYSUJIqgzz/sqZ4XN3yN1REYslUpLB084m0jKot79Pnfue38Zs+qUNlskeroqxhOvDgeygjznFH01qlmbZI+LUx7wB+pRLl51jT0xDLcG/hO0w3liih8ZVb78RbWORrUg25bTpDwja7EpFupZmQiExPT2PJydfrFZHBpaquRUhEmgvr27j3GyzDYiwhtvd6N6wqInKAEU+JBSNs4W0pIv3fkSe2kay6nYF3IQzdiILNvjEvau++niVh6Nj6zk5buy3UzJAhZhOTQobdLN69HduZObNbisikbWHuQKIOjarZNURkKd7aztjNLaPqLVO9+1tCRWQQnTP9IDuW4J2/9Ap+7BdfHv1uo9bdXrC2hde9ehX3kgh5M0dH24jIN3Bluc5qK7/d9tIJzjg6t8YNzJE4lMI0TPG5ZS0ZDW9vrIhAq413MyIS+kMufftJnvvyF9E0jUMvm8O3K9HEWu81/5JqU7xnHKLSTIci0oWIuNIfoqfTwnAdy6ET8KbFzwPwuXsfxMvneexFQdLuPSo+f8dxSIRERAYJtisiYQtvOxGxLUFE1npE7CNp0q8+QvzW7oRtJ1gbbb/fcVAMq4qIHGDE1sS8t8yq21FE+p81U9pGqmo7Qp/IC3lRE/eNnbXuhrDsFhHRZR2arHivzQbetSPyifTRwjtoReT2VBwduC+b3PKxm6EgSzOZcbHPEzJLZCnWOk/MM2d4ZlZs/209lmagbfDdHnXOmG3lt52UZkJFpOTWMbJSHfna18R7jI7C5J3igTPfwK2JRd1oC97TK01ujRskcw66Y7QUkUAQ+5zM76hbHqmRTYjIJsFmrXj3aXzf468+IVqRb3nlg8RH6vhmRSgiQFmWN3RDw2w08boqIusX5agsI0P9kOfIm+f+HIAv3nUfDdPisXOCPNx3rEVEWopIDoChoSE0TcN1XUqlEr7vMyOJzvT0NHaoiLidWSPOsQzZ1x8ncff4hsdpu7ieFBGA6eTBMKwqInKAsTbUrFKUpZlttO9uRxHZzpyZdoSdMyFEquoAiEhYmnGX4dX/DF769+HmNxIEQVtpZuOuGWhr4e1HESkMVhE5k4zxjYdu49/dcmxHr5OXpZlQEZkKFZGhFhmbmzhBpeERs3ROjPZOpAY9+G4n2JkiIj6zaqEQleUqX/kqsEYRmf8OtdC/0VaObEp/jTkiM01Cj4gcWJY0W4pIamh4w+0IZ85spYh86zOfZuHCOZxkkge///vFW1llmrLttSwTXpNZh6DSxLfWExFrzbwZaDOqTosFEEccl/sK32HKNqjE4vzN7ffy1IJ4ve5EZFi+l0lOxsIvLS2xsrJCvV7HNE3GxsYiIuL7dTzv2oSLtWbsXB9EZColrlNXS9d3qJkiIgcYLUVEeER2YlZNRV0z114RCRHoO0tVDWFHoWYrcPwheOMvg53AdZcJggag4Tjdw8xCtLfwrk2G3Ah+KUxVHYwiAjC2w7IMtDwiWdmuGKarLmXEQqAnEjzrid/dPJHG6OP9QiIyqMF3O0FLEcn1/dyQvFeKeewwWfeCmJ5rjo3C0HFwsuA1qKyIhTvsVgNoyg4eK0x5DRURGdSXCIRHxE9aHWbXtZg4GRpW59cZVkMiogejfOGT/xmAl3///0J6SLby6h5eRZyD5VXxvsmcg1dutCki60szbptZtT1DRDzIBjOOTsCbs+J7/icPvgovgOlsjOmc2F9BRGQLd7ylSLWXZ8KyzOTkJIZhYBgJdNlG3i3UbDdgjanSzF5AEZEDjHZFpOm6NKriQrCt9l3ZSVHuo2sm8ohsM368myKS28GcmRBR10yj02ke+kNsexRd39wIZx09CoaBXy6v6yrYCJEikh6MIjIIBL4fZYhkxgQRCUszy9Jo6tx0E0/PiW3vtWMmRFSa2UeKiLkDj0i10CIiIYzRUaF+TInyTHlFnFee2xrP7pzIknr4MLGzQyJLJlREXEEAHF/4SbzU5ue3k0gyNCVIQLsqEgQ+tZpYjL75Z1+nWsgzPH2Yu777ezCMJCC+vw2Z5tpORJqVMuhC6exmVvXzefyaUDPcKEOkTTEMyzNx8ZpP3XQznzhb4xe+747Wdncxq0KnYbXdHxIiVEVc99oQkfbSTK83GHuJg5IloojIAUZERMrFSA3RDQMn2b+nIOyaqbk+nt/bF3THisg6IpIdTGkmmjfTSUR66ZgJods29mGxfb36RHZDEdkpyqsreM0mmq5H81ZCs+qC7OTYbscMtJlV94UiIrZhW4qIJCKe62IcPtTxtzCRk6m7aPg61aooe7j1WrSYxU7nyL3xBPHbRkXMuSfzZ2Rpxm7KsLD41pfk8S6G1UZjgSBoUM/H+OanPwPAq37sXRim6FgLCYbnFQiafkREUjkHN8p40SVpkT+l02gxcS6EpYp1ighEROQ+rch4rUolHmdOa/Cqm1sejm5mVeiuiHQjItdKETEkEQlcd1vTta81wiwRVZpR2LdoTeAttebMpDN9t9JCSxGB3rNESnJaama7HpG20oymmQRaYkClmZZZtR29hJl1vE6fLbz7URGJMkRGxtANcWxDIrKs2Tgvf4ihv/t3+op2b8dete92Q1SaMfs3q1qxGKYtVYvRzm6NcMYKU3ex2mjNtfE9j2aXIXpRWcZpK4PUxKW4bm8dTDXRJeo9LMvMfOkwvudx4p77OXH3fa3ttySRMit4ZZeSJCKJjIXni9KtaaY7rg2apq3rnNmMiOj1PN9dEoThz5xOsm3b9qaKyNLSUmRUnZpqqS1h58y1IiK6bYt4e64Pn0hoVi00CpTd/T2kbzMoInKA0Yp5L+7IHwLgmHrkDeg1XXW78e4hUnYquqO2zSxo2mC6Zto8Iu3yaz2Md98kzKwddp8tvFHXzD5SRAprjKoAo0kHU9fwA4j/6q9TPnqKuYJYuG6e3J4isp9KM9tRRKBlWG2kktBWIgyj0AUR6ZxXU6uUWIewLJOQhMZOo8u22qq5Ncmf7NI5U61doXApyep5C90weNWP/q8dzwm9H75Vxi82IkUk0R7vbq7/bNs7Z4Jmk+ac2Hazg4jI59XyvAGxH58dnqDe5pHpZlaFFhFZWFig0WhgWRajo62uIautc+Za4XrqnEnZKdK2uM5fz1kiiogcYMTbJvBWozCz7d2Na5oWJW726hPZ7sC7doTlGUOGUO1kzkyI0CMSBM1o/DnQc8dMiH5nzkQ5IvtQEWmfq6HrGuMywn02X+OpGbHdx0cSfZPKyKxaW93TmnsQeDTDQLNttO9CqzxTrZSxjxyJfm/K8gIjp1n1xGdrSMLcWDNZFmgREdnGipOGvFikq1oXBWUNWgmr85HSWSlf5soXxWd4zxvexPB0Z1nTMtsUkZIbEZG4pUepqlYXImK1KSLNuTnwfTTLapWjIFJEqOW5P5tkdGWJsmXzueXWd2sjj0g2m0VvywUKjaohrnVpBtrzU/Y/EYGDYVhVROQAoz1HpBJmiGyjdTdE6BOpXCNFBNrKM+bO58yEMAwnqoW7bT6RXsPMQoRZIvVz168i0goz6xzwFZZnZvM1vjMjFrt+yzLQMqs2gyYlt4s6cI3QbBYQk9JaZYp+0WFYlSTUyOXQwi4X3WDVEIuCKc/TWrmLXB4SkbA046QJlsXjSn51S8LWblidl+WZZz7/DeqrDnbS4sG3/+C655hWqIhU8EsNfOnziht611TV6Hlt82bCsow5NYXWHioYEpF6AXt0jIe//hUA/nB+tbXNttWViBiGwdBQ6+d2fwiwYajZbiJ2220kXvpSjOz+uWHYDAchS0QRkQOM9q6ZanH7qaoh+u2cCc2q280RgZYi4uviYjcIsyq0l2fWE5FezKoA9onjgJhG6ndbcNZg0Mmqg8DaePcQEREp1CKj6i19lmUAYmaMuCl8E9c6XbUdYVnGMFJbdkRthIRUsiqFfJSsG5VlJFY98Z1zTLHQ1zcrzdjSGOqkaS6K76cbuNS82pbbEuWJnHsBr+ny/OcESbjzb90becPaEZZdPLOMV3L50Z9/Oe/+t68iYXWPd4+e16YOdPWHQIciYo6N8qrHvwzAny3mo/JMXHfRJRFsJyLQMqxCFyKyB6WZ8ff9DMf+0ydIv+Y11+w9d4KDYFhVROQAI9ZWmmmZVXeuiPSaJdJSRLY/B+Vtp9/GI0cfoZl5HTCY0gy0DKsNaWAMgoBaj6mqIcyhoWhseP38+S0fP+hk1UEgvyZDJETYwjtbaJVmtqOIQJtPZA8NqzvJEAkRKSLFAs4ZQQTMqc4y3kpZKg268ErUuyoi0qxqimPsmmn8QhVdWip6mVQ8Icszsy88h2Fa3P2DJmN3LHHrq17Z9fFhaca3Kvgy1MwwdYKy2zVDJES7WbXVuruGiDgtj4g5OsptLz7LQ098lfdPD9MMu4YC2f6LBVanjyb0icB6IrLRvBmFFg5CC68iIgcYYWnG95qRF2A7GSIhkjJdtdxjuuogPCJHMkf41Vf/KgXzODCY0gyAZUtFRGaJNJsFfF/krPRKRKB3w6pfrxPIGST7RRHxfY+iHNmeWVOaCdNVLy5VeH5B3NVvl4iEnTN72cLruqE/JLft12gvzaTf8AbGfvq9jL//H7Xeo1GnVJRZPQgVqd7NI1KUc2YMocwU/SQaGo4rzu1ejtPaqPfvet1/43/5wKcZGXmg6+PXKiIh/LLbmjNjbUFEwlTVNeSrXRHR43HMZJJ/9Zu/wjt1l6T0ezi+OA4V4qxFSERs2+4gJdBWmlnTaq/QQpiuqoiIwr6EaTsYllAjVq7KyZw7ISJy3kylb0VkZyqG6weUPXG7mB1A+y6sL82EZRnLGsYweh8v7vQ4cyZUQ9A09G3kuOwGSstL+J6Hbpik2uRxaCkif/P8Ip4fkEtYUeJqvwgVkb0cVb6TOTMhogm8hTy6bTP67ncTu/mm6O/5Oamo6U0Smlh46+VupZnOybulpjjfEr4gJr0oImGWSHFxIVI7TTOFrnc/d9d6REJ4JTcyq5pGt9KM7CCZm+upNAOtXJXmYsvs6ciI9ioOfls3DcDRo0fRNI0zZ850GFeh3ay6TBBs3dp8IyI0q6rSjMK+hKZpUXmmuCQuCtvtmoHWvJleFJEgCHY8aybEarNFfAblEYnyCeQCVQtbd/tQQ6A9S2RzRSTKEEmlOo1+e4iCzIbIjI6h653HNSQdBalq3Tq1vfwZaFNE9oFHZFCKSDeszIqFIJfUiBniuNUrm5hV5eTdkiuJiCa9ND0oIk4iwdCUCFbrNndmLaxIEal0UUQkEemiiIRdM36lQv2558TvDq0lIjnx3zVExFtcbL2OJ8dMEMNtS5wFmJiY4L3vfS9vectb1r9/RBz96DNU6ERoVl2oLuD67haP3p/YH1dEhV3DWuPatVJE2hNYd6qI5JuC+GRMHWObi+FaRIqILM30G2YWwolKM1soIqWwdXf/+UMya/wh0DKrhug3UbUdB8UjEpL4sANtLVZnBZnNDWdwZGT6OiLSbEBVKkPyDr9YF5fhjCnOjV4UEegebLYRzLB91yp3KCIdpZkuZlU9mUSXJd4w1Gx9aablEQEwxkJFpEVEDLlPFWLUu4S85XI57C4zdnTdirb9WhpWryeMxEewdAs/8JmvXB8zctZCEZEDjlARCTEIj0iph66ZokxV1bTOVNbtIO+Ki3p2AHNmQrSHmkFbx0yPYWYhQkWkcf48gbexUhQqIsY+zBDJrumYgVZpJsQtOyEi+2DwndsU772dVNUQWykiq1IRGZo6jBMqImvNquWwLGNFMe/FmiDsWVu8fv9E5LktHxu2LPtmBb/SJPDEe3aUZroQEWj5RKKfN/GIQCtptrnQIiJadRUQikg3IrIZonkzyrDaFbqmR50z12uomSIiBxwdRETTiKW7X2x6QaKPHJH2OTPblfRDrEhFZGhAZRkAe828me2WZqzpaTTbJmg0ohp6N+xHRWTtsLt2xCyDoUSr22m7RlXYH4PvWqWZ7RPxkMS79RpuY/1iGikix2/B0TcozYRlmdQ4NES5olQVj83F+yNsLSLywpaPjWbNWBUIhBICa0ozXbpmoJOImGNj6GuVi7YcEYKgzSPSIiJUxWe/LSJyjWPer0dc71kiiogccMTaWkVjqfQ6L0A/6CdZNfKH7LAsA5B3xWsNyqgKbRN43Z2VZjTDwD5+HNi8PONJOX9fKSILYp/Xtu6GCFUR29A5NbZ9ArUvFJEBmFXteALdEOdzN1VkdU4SkZvuwzFF2aVeWEO+QqNqahxq4pwoyVLJSEos4L0qIuPHRQtvcWmBSn5108eG5Y3ArBFoTbxSg8D1CepeRES6JatCy7AKXYyq0CIigQ+NUisivYOIiO/ZdojIXsS8X2+43rNEFBE54GhXRBI7XAS3pYjs0KgKsNoMSzO7QURCs2p/GSLt6MWw6hfF3e/1oohAq4X39HgK29z+pWJ/KSK5bb+GpmmRT6S6xifSdF0Kskskd+g4zrBYsOvF1c4XiRSRCagLlaxUFERgJC0+h16JiJNIMCSj3LfyibSrHZ5ZxS+5eFIV2ao0Y7UrItNdxh+YMVFqgijUDNbMatmJIqKyRLbE9Z4loojIAUe8jYjsxKgKkHJ6V0SKA2rdBViVHpGhAYWZAdgyR6TZLOL7jbZU1d7mzLSjF8OqV5SKSGr7pbFBwms2Kco71o0UkdCwupOyDOw3s+r2FRFofYcqaxSR/PwsBAFWLE4im8OZFIFn65JVi+1EpIAXaJTLgghMDInFJN/ojYhAK9hsKyKi62Y01sC3ynjFBn7ZJdCaBIZQZHopzXRVRDStM121W2mmIhSRCnEajcbaV9gUexHzfr3hep83o4jIAUd7aWYnRlVoa9/toWumpYhsP1U1RH4XFBEhVYvTv1q9jCfbCx2n+6K8GVozZzYmIpEiktkfRKS0vEgQ+BiWRTKb6/qYN985zZnxFN9/3+Guf+8VYWmmUC/Q9HvLoBk0BqGIwMaG1cgfMjmFpmk4h24DoF5b005Z6iQi5aYNARimyXhOLCb9lLAmT4VR7710zrRaeP2Si19q4MmOGRDx912ftxURgTYiUsAcHyd2223E77ijNTcnUkSc7SsiqjSzIa73ULPB3WIq7EvEOhSRnd3Zhl0zlR5yRAbpEVmROSKDJCKapmNZOVx3mVLpO4C4UJtm/2FjvaSrRorIDszCg0Q+yhAZ3zDX5OWnR/n0+7pHhveDrCP9CQQUGgWGY8NbPGOw8Lwavi8ixneqiCQ2UERCIjI0IRYE5+jdwF/R9EXZxpTBghERSY5BvUjRFdkhyaERsjKPo9fSDMCEDDab7TFLpF6fwbcqeKUGetmK/CGGkUTXu39X+yMiecxjI5z4r7/f+feIiMS37xFRisiGiMyqpRmCINhxg8C1xq4pIufPn+fHf/zHOXHiBPF4nFOnTvGhD32ob1lOYWeIJds8IjtVRPoozQwqVRVa7buDLM1AyydSLAoish1/CIAjzare8jLNle7lh5ZHZJ8QkS2MqoOEqZtkbEGC9yLULCzLaJq54V1/r4hHHpE1RGROhplNCiJiH7sv+ltj8XLrgaFZNT4MfjNKVU2PjERemnw9v+UE3hDjJ06CplFaWtzasCo7hjyzLBURF38Lfwj0SkQ6s0Q64PsgP3fVNbM7CM2qNa+2pyXQ7WLXiMjTTz+N7/v85m/+Jt/+9rf51V/9VT7+8Y/zT//pP92tt1TogvbSzE49ItGsmR7MqoOYMxNiN0oz0GrhLUpFpN+OmRB6MhllKzTOne/6mP2miLSMquszRHYDYXlmLy6SYVnGNLM7vlNMpENFpNOs2irNiIVaT+SwDdE5U7v4eOuBJTlnxhHfyzBVNTU0EilHXuBRcrtEw3eBHU8w3GPCaliaCRURv+xGpZmN/CEgiIgWi6FZFtahDcp0a7JEOlDPR+FtO8oRUaWZDWEbNqNx4c25Hsszu1aaecMb3sAb3vCG6OeTJ0/yzDPP8Bu/8Rt89KMf3a23VViD2ADNqmGyak8eERloNghFZCVSRAZLREKZfqeKCIBz4gTNmRka514kce896/7eUkT2R/tuFGY2vv197gc5J8cFLuxJ58ygjKrQPoF3Y49ICMcxaVR8Gpe/BQ+8HYKgpYjICbTFQBCS1MgoMTNGzIhR82rk63nSdm+kdeLkaZavXmb2xec4cc/9Gz7Oaht85xdF14xvipyTzRQR3bY58vGPg+9hpDYoXUZZIl2IiDSqekYczzO2TUSEsby+4TydjbC09NfkC0/gezV8v47ni1Kd7ze6/s6Tv7vpzD9jYuJNfb3XXmI6Oc1idZGZ0gy3jdy215vTF66pRySfzzM8vHF9uF6vd5ykhQ2ilBV6R2f77mAUkXrTp+n5mMbGglpoVt3pnBmA/C54RKA9XVXcaTmx/jtmQtgnT1L+4hepb9A501JE9kf7biGMd79Wisgeds64zZ1P3g3RzSPiNZtRXH47EYnFExQrJWozz4hf1AvQFF6VaPKulwAgPSzuZrNOllpFEJHD6d5MwhMnT/PUFz67ZbBZWJrxrQreYgOjI1V1c4KcfLD7VN8ImykiMlW1aaehSt9ExDQzaJpJEDRpNJaJ9fk9XVz6LJcvf6Kv54AgPtcTJpOTPLn45HWZJXLNiMjzzz/Pr//6r2+qhnz4wx/mX/7Lf3mtNumGgB2Po+k6ge/v2KwaekQAKq5HZhMiUqwN0COyW6UZq5MUb7c0A1sbVvedIiJLM9kNMkQGjSjUbA89IoMgIt08IoXFeQLfx7QdUrnWOWWns7BUoj5/XvwiVEOcTBTvHnpEUsPirj/rZJmrzPXVORMlrG7ROdPRNVN2RXlGlmY2CjPrGc5mREQcf9/JbYuICGP5MI3GPA13qW8iksvdTxC46HoMXXcwdAddd9CNGIb8nfib3fG7WGwDP8w+xfWcJdL3KvGBD3yAX/qlX9r0MU899RRnz56Nfr5y5QpveMMb+IEf+AHe9a53bfi8D37wg7zvfe+Lfi4UChw5cqTfTVRog6ZpnLz3JSxdvsjQ9KEdvZZt6Ji6RtMPKNebZDZpzY1yRHaoiFQ9n5ocnjdws6rdSUR2VJoJZ850UUQC38cvCSKyHxSRputSWhYq0LUwq0JrAu9eKCLNqHV3gKWZNrW2o3W3rQPJyY0BV6jnl0SKalH6Q9rDzBrinE6PCCLSbljtFeMnTkWG1fLqCslc9/20Io9IGQJozlfxj8iumU1KMz1hU0VElGYCeQ70S0RAlGcajfltZYlMjL+RifE39v286w3Xc5ZI31f297///bzjHe/Y9DEn5UUZ4OrVq7z61a/m5S9/Of/+3//7TZ/nOA6O01/9T2FrvOUf/XMIgh2Pn9c0jaRjkq+6WxpWSwNSREI1xNAgtYkCsx2sXZh2QkTCLJHG5cv4jUbHPA6/XBb+AEDfoSo1CBSXFsRMEMfZsW+oV4Slmb1RRMR7DrI0U6+U8ZouhmlFw+5yE5136rG02Oe6b8DsN9elqgYBlOrCPNuuiEB/WSJ2LM7w1CGWr15m7tzznLznJV0fF8a8+45QQYKGhxfFuw+KiHQpp0tFZEdERHXObIkbioiMjY0xNja29QMRSsirX/1q7rvvPv7jf/yP6DtcCBW2B03TRPrhAJC0DfJVl8oWLbxRjsgOFZHVNn/IoHvj15VmduARMcfH0JNJ/HIZ9+JFnNOno7/58u5Zsyz0fUC0W1N3J65Z3kAU874nXTOyNGPmdvxasWQqKnVWCwVSwyOszHa27oawE8LYWfdMmPlG6w+pcagXqXgWfgBoGklZ0gmJSD/pqgBTN53FsG0C39/wMaYlSzNOK8TMt7bumukJmyki0qyqJUIy0X+Egwo12xpRaeY6nMC7ax6RK1eu8KpXvYpjx47x0Y9+lIW2uQOTk9fGqa8weITzZrZURKIckZ0lq4bx7jlz8KdquyJiGMkdZUxomoZ98iS1b36T+osvdhARrxSmqu69GgLX3qgKbe27e9I1swoMRhHRdJ14OkMlv0qlkCc1PNIKM5vs9BTEkpKI+JKIyFkypCagVohad5O5IQx5fm+nNAPw+ne/d0tSaYWKiNWaCNxLjkhP2CxHRCoielKQre0oIirUbGuE6aor9RUqboWEldjjLeodu0ZEPv3pT/P888/z/PPPc/hwp/u717Aehf2HaALvFi28gxp6t1tGVWjdZYEoy+xUHXBOnqD2zW+uM6yGioiR2nt/CLQyRK6VPwRaC+xeTOAdZPsuEBGR0CfSrXUXwIkUEQNmnwTtLvGH9ARUlik2RfkuNdQ6D7N2/6UZoKdzNyQbnlGJfheWaXZVEZFExEiNAXmazSbNZhOzj5sLNW9ma6StNEkrSdktM1uZ5WT25NZP2ifYtVrJO97xDoIg6PpP4fpFMlRENinN1JseDU9IxDv1iESKyIAzRKBzYdpJx0yIyCeyZuaMV9xfikhYmtlo6u5uIIx13xNFpLkKDEYRgbYW3mIe3/Oi47mOiCQF8az7Jiw8DSvnxR+kRyRUREKjKrSVZvpURHpBlKyqlQgQ1+GBl2bqhcgPFUGaVY30aPSrvgffqdLMltA0reUTuc7KM8q0odAXEj3MmwnVEBgAEZEekdwuKCKGEUfXRbDUToyqIcIW3vpaRWSfZYiEmRfZa1iaCbtmKs0Kda9/aX4nGGRpBjoH3xWXFvC9JoZlRVkgIZyEkMbrxEWy6OWvij+kxqFeaCkiw9eGiISlGTSfwBB5JqFZdeelGfnaXqOVlRIiLM0kRrDkzJ1tD75TisimCInI1fL1lSWiiIhCX+glXTX0hyRsA0PfWbkjVESyA27dDREaVncSZhaivYW3Xfnz9lmGSOEap6qCkI0NTZw717JzJgh8XDcMNBtQaaaNiKzIskx2fHJdV5qTkIqIJtNIw8nDoSISZYi0CMx2PSK9QNdjaJogAmGQmW/0Fmi2JewUaHL/15ZnpFmVxHDUFakG3+0OrlfDqiIiCn0h0cO8meIAU1XfdWSMv7j/Jt5zpLdOrX5h2WJxGkRpxjp6FAwDv1ymOd8yZ4eKiL4PFBG3Uae8Ku5Qr6VZVdO0PemcaTYLgCgTDq40IxbtSiG/oT8EwInMqmsM26nJNaWZ9URkN7w0mqa1hZqVCfDxNElErB0SEU0TQW2wnohIRYT40LaJSOQRcZdUeX8TXK8tvIqIKPSFlFRENmvfHeTk3WHL5PZ0gmPx3Wl7HRp6ObrukM1tPKOjV+i2jS2N2e0+kVARMfaBIlJcFATJjsc74v+vBfaicyY0qoox9/YWj+4N7aFmYYbIUDciEpZm3LaFUzMgMQy1QlezakYu5sVGEc/ferhkv7DaYt59swaa2DbTGMC50C1LxPdaxCQ+jC3zdfovzQjlUsyC6W0g4I0IRUQUbghEishmRCTqmNlZ6+61wJnTH+CVD3+dVPLMQF7PluWZ9pkz+0kRaTeqXqsMkRB70TkzaH8IdM6bWZ2TisjE+jjw0KzaaLj4IRdJjoFuENQ2N6sGBBQbg5910q6I+NIfous2hjEAot+thbeWB2mMJZ7btiJiGAkMQxA7VZ7ZGKo0o3BDIPSIVDYpzURhZgNQRK4F+p3muRm6zZzZT4rIXmSIhNgbRWQVGCwRiadbHpFNSzOJVo5DIwzPS4njXq+UcAPxXWo3q1q6RdISJZ3dIGytmPcKnjmgjpkQ0pBMuwcoLMvYaTCsbRMRAMtSnTNb4UT2BP/o/n/EP37JP97rTekL18dKobBvECoipU3MqsUBlmauN3SbORPmiOwnReRaZoiEiGLe90IRMQdjVIU2j0h+FbchFtTc5HpFxDAtTMehWa9TH7mN2NznhVE1CCiVRftqLJHAcmIdz8s5Ocpuue901V4Qkg4/XsOvDqhjJkS3LJHIqCqOf0hEtpuuWqtdUlkimyDrZPmx235srzejbyhFRKEvhOSil/bdnYaZXY8Is0Tq59oUkXDg3T7IEbnWU3fbEQ2+u5aKyIAzRKDlEamVS3iui26YZEa7m6nDULNa9ibxi8wUuBVKrvhupEZG1z3nWmSJGCd09COiNDc4RaQtSyREm1EV2JEi0mrhXd7+NirsS9x4K4XCjpAIk1U3Nau6wI2piNgnjgPQnJnBL5fF/JlQEdkHyaqFeTEBNrOHisi17JoZdKoqiGTVdmTHJ9CN7jk3TiJJeWWZ+sm/BfEqvPTvQ71IsUvrbvR620xX7QVhacY4qpG8bRieGiAR6dY1ExER2Sa/EyKiSjMHFkoRUegLYbLqph6RAbbvXm8wh4YwhuVMjfPnAaWIhAgVkWuZIxKWZkIlYBDQDaOj46ibPyRE1MJrpOBtvwGTt3fMmUl3UUR2M0skJB1NtyBbm3e5NCNTVQehiKgskYMLRUQU+kIvisiN7BGB9YbVliJybdtl18Kt1agWxCKxJ2bVPVVEcgN93bA8A1sQkXDeTLk1aE4oIutTVUOEpZndUERCQuY289eIiAywNCMNv8ojcvCgiIhCX4hmzWyWrHoDe0QAnLaZM369TiCNeUZmb4lIGO3uJJPEkte+TBR2zeyFIjLI0gy0DKvQvXU3RHci0lJEupZmdtMjEioizQLNZrHjdztGtxyRtlRVGJBHRJVmDhwUEVHoC62hd1u3796wisipMEvkHH6xlQWhS5l+rxBO3b2Ww+7a0a6IXKt0zN1o34VWCy90DzMLEQtLM5VORaQkFZFrXZqxuhKRQSkim3lEVGlGYWMoIqLQF5KyNNNo+rhywu5aRDkiN6oi0tbC60kioqdSaBsYGq8V8tKouhf+EGh5RFzfpdKsbP7gAWE3zKrQCjWDzUszdqIbESm0mVX3pjTTdAu4UWlm0IrIxmbV7SarQptZVRGRAwdFRBT6QpgjAhu38EalGWf/J6vuBsJ01cb58/h5cVHW03tblgEYOXyMu173tzhx93178v5xM07MEJkZy7Vr04LZyhHJDfR1Q4+Ipuub+m26lWbc8io1T3w31k7shd2ewCtIh9vM40lFxNpVIjI4s2pYmnHdFYJg8PH3CnuHG/OWVWHbsE0dy9BwvYByvUk2vp5s3OhmVWtqCs1xCOp1ak8/A4CxD4jI0dvv5Ojtd+7pNuRiOWbLs6zWVjmSPrKr7+V5dXxfpIfulkckMzaOYW5MuLuVZkrL4o7eNLSoq6Ydu9s1I2fN+DUajUX5uwGbVXcpR6T1Gfq47mpETBSufyhFRKFvRC28G3TO3MjtuwCaYWAfPw5A9RvfAPaHIrIfcC07Z9ymeA9NMwa32EpkJ0Q5ZuzoiU0f53QpzZSWhUqQTtpd5/1EisiuJKu2TMrV2hX5uwHniLgVaMrk1Ir8nNeYVRuNRt8+IV23MKWypcozBwuKiCj0jWQ4+K5LlkjT86m64vc3qiICrRbe6pNPAvtDEdkPiDpnrkHMe5QhYmYHPuDvxD338b3v+6e89u+9e9PHdSvNlPJCMUilY12fEyoiZbeM67kD2NoW2klZOMV2YCTNaSM09QJ4TQhVnTWKSBAEuG7/+6Y6Zw4mFBFR6BubZYm0k5PkDUxEohbeF14AlCISIlxkr0XM+24ZVQF03eDMAy/vajZtRxRoVmmNri8WhFE3tcHsoZSVQkMQp91RRbJrfh7QuWmYYrgdCJ9Iu1dEGpUty4pI4Y58IkoROVBQREShbyScjRWRoox3d0wd27xxT6/QsBpCKSIC11IRabpiIRx0624/cBKCbNQrrS6hUrkGQDrXvSRi6AYZqS7sZpbIRj/vCO2G1dCo6mQFSQE0TRtMzLsiIgcKN+5KobBtpByhiHTziNzorbshnJOd3gGliAgcFEWkVziJBCBKM6EnoliWs5iGNt6u8Djt5rwZAR3DGGC+TXuWSGRUzXU8ZCBZIqo0c6CgiIhC30hs4hFpte7e2EQkNKuG2OtU1f2CyKx6TYjIKgDWmlLEtURYmgkCH7cmOnhKVemh6hJmFiIcfLebE3hBlGUG6p9pV0TWpKqGGMwEXkVEDhIUEVHoG2GoWTdFJGrdvcEVET2RwJxuBV3t9ZyZ/YJra1bdnTkz/cC0HXRZlgjLM6WaWPjTY5MbPu9axLyv/f+BoKM009m6G2IQpRnlETlYUEREoW+EHpFSl3kzShFpITSsglJEQoRE5Jq07+7SnJl+oGmtrJB6uYTveZRdQeRTYxvPqNnNdNX20szAwsxCtGeJrElVDbGjdFVVmjmQUKuFQt9IRTkiXUoz9Rs7VbUd9smTlP/mbwCliISIvA/XYPCd2xTvsZeKCAifSLWQp1YpU15ZJkBDxycxujEReenkS3EMhzNDZwa+Pe0qiGEOePih02XezAAVETVv5mBCERGFvhG173ZRRIo1YcS70c2q0GlYVYqIQKiI5Bt5PN/D0Hdv/s5+MKtCW+dMuUzRuwxA0mygrzFxtuNtZ97G2868bVe2p90jsmuKSC0PgZxFtQulGUVEDhZUaUahb4SBZl0VEVWaiWC3lWZU14xAWHLwA59Co7DFo3eG3Zq82y/C0kyjUqY0L4hIymqAFd+T7Wk37w46cfZamVU9r4Tn9f98hf0JRUQU+kZCtu9284gos2oLdpsioqcGLIFfp7B0i7QlFr/d9onsB48ItFp4a5UypQUxATnt+DDgtNde0U4+ds+sWtjSrNpoNPp+edPMoGni2uIqn8iBgSIiCn2jpYgos+pmMMfGSL3mNSRe9iDm6Matmjcaos6ZXfSJBIG/fxSR9tLM0gIAqdjeXXqtjvbdQRORbjkig1NENE1T5ZkDCLVaKPSN5CbJqirQrAVN0zjy7z6215ux75CL5bhYvLirikizWQSER2HPiUjbBN5w8m46uXffj8723V0szTSK4v8H6BEBYVitN+ZU58wBglotFPrGZjkira4ZdWopdEcYarabiojnlXGcKXy/ga47u/Y+vSDWNoG3uCq6SVLJvdsm09xNRaSNiNSlB2jARETNmzl4UKuFQt/YdNZMLVREVPuuQndEMe+7qIjEYtO84qEv7Nrr9wO7bQJvKS9UglR6b4yqsEYRsQatiOTEf6vL4Mr5OgM0q4LqnDmIUB4Rhb6R3GT6rlJEFLZCFGp2DWLe9wNi7aWZklic09kBKxF9wDCcSCUyjQETkTBHJCQhaC2VJHzIgBQRVZo5OFBERKFvhB6RyiazZpRHRGEj7OZAt/2I0COyOnsVzxOD71LZvZt/A+DYE+K/zvhgXzi2hmDFsrAmK2YQHhFQishBglotFPpG2DXT8HwaTR/bbPFZpYgobIXhmJDqbxRFxIkLIpKfnwMgYTQwEnuniADccusvUym/QDJ5erAvbDpgxqEpBvyt9YfAziLeARx7FMsaQtftbW+mwv6CWi0U+kbcbt3hVBpNbFNcEHw/aBERpYgobIAbVREJkTIb65WDa4yh3EsYyr1kd148loXSxkQkVESazSae52EY/aXrTk29nampt+94MxX2D1RpRqFv2KaObYhTp9yWrtruGVGKiMJGuNE8IuuIiFVveSkOItpJ1hqjKrSICGxfFVE4WFBERGFbSMp01UpbumqohliGhmOqU0uhO244RSTRmaqbNuvgHODI/3ZzahdFxDAMTFOWd7eRrqpw8KBWC4VtISF9Iu2KSHuqqrZH8dUK+x+hIlJySzS8g78Q2bFYR5x7ymoccEWknYisV0Rg54ZVhYMFRUQUtoVuioiaM6PQC9J2GkMT58+NoIpouh7NmwGliIAiIgqduCZEpF6vc/fdd6NpGk888cS1eEuFXUaoiLQPvmspIirMTGFj6JoeTeG9YXwibeUZoYgcYCLSrvYoIqLQA64JEfkn/+SfMD09fS3eSuEaITSjVtpLM+GcGWVUVdgCUcz7DaCIAB2KSMo86GbVNkWki1kVFBFR6MSuE5FPfepT/Pmf/zkf/ehHd/utFK4hEl3SVSNFRJVmFLZATkaB72bM+35Ce+dMeh+07+4qVGlGoU/s6ooxNzfHu971Lv7gD/6ARNsdwUao1+sdJ2ahUNjNzVPYAbqlqxZVmJlCj7gWg+/2E8LSjK03sQ3vYJdmlFlVoU/smiISBAHveMc7ePe7383999/f03M+/OEPk81mo39HjhzZrc1T2CFCRaSrR0QpIgpbIFJEbhCPSDhvJm3WQTfBjO3xFu0iOohIrutDdpquqnCw0DcR+cAHPoCmaZv+e/rpp/n1X/91isUiH/zgB3t+7Q9+8IPk8/no36VLl/rdPIVrhJZHpD1HxAWUR0Rha4SKyI1SmrGlIhy17h7k9nZVmlHoE32vGO9///t5xzveseljTp48yWc+8xkeffTRjhQ9gPvvv58f+qEf4hOf+MS65zmOs+7xCvsTXXNEVGlGoUeEWSI3SmkmnhaekAPfugttREQDqXythSIiCu3oe8UYGxtjbGxsy8f92q/9Gv/qX/2r6OerV6/y+te/nk9+8pM88MAD/b6twj5D1xwRVZpR6BFhuuqNoojc9spHKJ17knuXHgPn1F5vzu4iPSn+m5kGvbvoroiIQjt2bcU4evRox8+plDBrnTp1isOHD+/W2ypcI7RyRJQiotA/IkXkBmnfzYyO8bo3vAR+/98d7I4ZgNxRePv/BdmNPX4hEVER7wqgpu8qbBORItKlfTetFBGFLRB5RG4QsyoA9aL470EvzQDc8f2b/lkpIgrtuGYrxvHjxwmC4Fq9ncIuI7mpR0QlqypsjvaumSAIbozZRDcSEdkCiogotEPNmlHYFhLKI6KwA4SKSMNvUG1W93hrrhHqMhfpIKeq9ghFRBTaoYiIwrYQKSLtOSLKI6LQI+JmHMcQi9GNYlhVikgLiogotEMREYVtIfSIhKWZIAhas2aUIqKwBTRNizpnbpQW3pYioohIOxFRJXsFRUQUtoXkmkCzmuvj+eKCohQRhV4Qds7ceIqIKs2EyapBEOC67h5vjcJeQ60YCttC2L7regGNpk9RpqpqWiv+XUFhM/zDe/4hDa/B2eGze70p1wY1qYgc9PbdHhASERCqSPvPCjceFBFR2BbayUa53mzNmXHMG6MDQmHHePjww3u9CdcWyiMSQdM0HMeJBp2m0+qY3MhQpRmFbcEydGxTnD7lRjPqmFFzZhQUNoAiIh1QhlWFEIqIKGwbrcF3XqtjRhlVFRS6Q7XvdkClqyqEUEREYdsIyzPleksRUUZVBYUNoBSRDihFRCGEIiIK20YrS6RdEVGpqgoK6+B70CiJ/1eKCKCIiEILiogobBuJKEukSakmumZUhoiCQheEagiorhkJRUQUQigiorBtpNqyRKIwM1WaUVBYj5CIGDaYzt5uyz6BIiIKIRQRUdg2Wh4Rj6KKd1dQ2BjKH7IOiogohFBERGHbaJ83U1ID7xQUNobqmFkHRUQUQigiorBtJNrmzaiBdwoKm0ApIusQpqkqIqKgiIjCthEqIpU2RUSZVRUUukApIuugFBGFEIqIKGwb4eC7cqPdI6LadxUU1kEpIuugiIhCCEVEFLaN0KxaaSiPiILCplAD79ZBJasqhFBERGHbiBSRelN5RBQUNoNSRNZBKSIKIdSqobBttLfvRjkiShFRUFiPu38QDt0Hmem93pJ9A0VEFEKoVUNh2+gINFOzZhQUNsbwSfFPIYIiIgohVGlGYdtIyK6ZlYpLw/MB5RFRUFDoDSERcV0Xz/P2eGsU9hKKiChsG0mZIzJXqLV+ZysioqCgsDXCHBFQhtUbHYqIKGwboSJSbwo1JGkbGLq2l5ukoKBwncA0TUxTXkNUeeaGhiIiCtvGWj+IKssoKCj0A5WuqgCKiCjsAGHEewhlVFVQUOgHyrCqAIqIKOwACWsNEYmpVFUFBYXeoYiIAigiorADmIaOY7ZOobRSRBQUFPqAIiIKoIiIwg7RXo5RpRkFBYV+oGLeFUAREYUdot0nosyqCgoK/UApIgqgiIjCDtGeG6IUEQUFhX6giIgCKCKisEOE82ZAzZlRUFDoD4qIKIAiIgo7RFJ5RBQUFLYJRUQUQBERhR2iozSjFBEFBYU+oIiIAigiorBDdJhVlSKioKDQB1SyqgIoIqKwQ7QrIsojoqCg0A+UIqIAiogo7BCdiohKVlVQUOgdiogogCIiCjtESrXvKigobBOKiCiAIiIKO0TCUaUZBQWF7UElqyqAIiIKO0RS5YgoKChsE+2KSBAEe7w1CnsFRUQUdoR2RSSpSjMKCgp9ICQivu/TbDb3eGsU9gq7SkT+5E/+hAceeIB4PM7Q0BBvfetbd/PtFPYAKWlWjVk6lqF4rYKCQu+wrJbBXflEblzs2i3sf/2v/5V3vetd/MIv/AKvec1raDabfOtb39qtt1PYIySkWVV1zCgoKPQLXddxHId6vU69XieVSu31JinsAXaFiDSbTd773vfykY98hB//8R+Pfn/rrbfuxtsp7CFOjiVxTJ3bpjN7vSkKCgrXIdqJiMKNiV0hIo8//jhXrlxB13XuueceZmdnufvuu/nIRz7C7bffvuHz1p6MhUJhNzZPYYAYT8f48j99rfKHKCgobAuqhVdhV4r6L774IgA/93M/xz//5/+cP/7jP2ZoaIhXvepVLC8vb/i8D3/4w2Sz2ejfkSNHdmPzFAaMXMJW/hAFBYVtQcW8K/S1enzgAx9A07RN/z399NP4vg/AP/tn/4y3v/3t3HffffzH//gf0TSN3/u939vw9T/4wQ+Sz+ejf5cuXdrZ3ikoKCgo7GsoRUShLz39/e9/P+94xzs2fczJkyeZmZkBOj0hjuNw8uRJLl68uOFzHceJTkoFBQUFhYMPRUQU+iIiY2NjjI2Nbfm4++67D8dxeOaZZ3jFK14BgOu6nD9/nmPHjm1vSxUUFBQUDhxUuqrCrjgMM5kM7373u/nQhz7EkSNHOHbsGB/5yEcA+IEf+IHdeEsFBQUFhesQShFR2LVWh4985COYpsmP/MiPUK1WeeCBB/jMZz7D0NDQbr2lgoKCgsJ1BkVEFHaNiFiWxUc/+lE++tGP7tZbKCgoKChc51BEREH1XCooKCgo7BkUEVFQRERBQUFBYc+giIiCIiIKCgoKCnsGRUQUVC63goKCgsKeYWRkhIceekg1MtzAUEREQUFBQWHPMDIywute97q93gyFPYQqzSgoKCgoKCjsGRQRUVBQUFBQUNgzKCKioKCgoKCgsGdQRERBQUFBQUFhz6CIiIKCgoKCgsKeQRERBQUFBQUFhT2DIiIKCgoKCgoKewZFRBQUFBQUFBT2DIqIKCgoKCgoKOwZFBFRUFBQUFBQ2DMoIqKgoKCgoKCwZ1BEREFBQUFBQWHPoIiIgoKCgoKCwp5hX0/fDYIAgEKhsMdboqCgoKCgoNArwnU7XMc3w74mIsViEYAjR47s8ZYoKCgoKCgo9ItisUg2m930MVrQC13ZI/i+z9WrV0mn02iatuljC4UCR44c4dKlS2QymWu0hXuDG2lf4cbaX7WvBxc30v6qfT246HV/gyCgWCwyPT2Nrm/uAtnXioiu6xw+fLiv52QymRviZIAba1/hxtpfta8HFzfS/qp9PbjoZX+3UkJCKLOqgoKCgoKCwp5BEREFBQUFBQWFPcOBISKO4/ChD30Ix3H2elN2HTfSvsKNtb9qXw8ubqT9Vft6cLEb+7uvzaoKCgoKCgoKBxsHRhFRUFBQUFBQuP6giIiCgoKCgoLCnkEREQUFBQUFBYU9gyIiCgoKCgoKCnuGA0FEPvaxj3H8+HFisRgPPPAAX/nKV/Z6k3YFP/dzP4emaR3/zp49u9ebNRD89V//NW9+85uZnp5G0zT+4A/+oOPvQRDwsz/7s0xNTRGPx3nkkUd47rnn9mZjB4Ct9vcd73jHus/6DW94w95s7A7w4Q9/mJe85CWk02nGx8d561vfyjPPPNPxmFqtxk/8xE8wMjJCKpXi7W9/O3Nzc3u0xTtDL/v7qle9at1n++53v3uPtnj7+I3f+A3uvPPOKNjqZS97GZ/61Keivx+kzxW23t+D8rmuxS/+4i+iaRo//dM/Hf1u0J/tdU9EPvnJT/K+972PD33oQzz++OPcddddvP71r2d+fn6vN21XcNtttzEzMxP9+8IXvrDXmzQQlMtl7rrrLj72sY91/fsv//Iv82u/9mt8/OMf58tf/jLJZJLXv/711Gq1a7ylg8FW+wvwhje8oeOz/t3f/d1ruIWDwec+9zl+4id+gi996Ut8+tOfxnVdvvu7v5tyuRw95md+5mf4oz/6I37v936Pz33uc1y9epXv+77v28Ot3j562V+Ad73rXR2f7S//8i/v0RZvH4cPH+YXf/EXeeyxx/ja177Ga17zGt7ylrfw7W9/GzhYnytsvb9wMD7Xdnz1q1/lN3/zN7nzzjs7fj/wzza4zvHSl740+Imf+InoZ8/zgunp6eDDH/7wHm7V7uBDH/pQcNddd+31Zuw6gOC///f/Hv3s+34wOTkZfOQjH4l+t7q6GjiOE/zu7/7uHmzhYLF2f4MgCH7sx34seMtb3rIn27ObmJ+fD4Dgc5/7XBAE4nO0LCv4vd/7vegxTz31VAAEjz766F5t5sCwdn+DIAhe+cpXBu9973v3bqN2EUNDQ8F/+A//4cB/riHC/Q2Cg/e5FovF4MyZM8GnP/3pjn3bjc/2ulZEGo0Gjz32GI888kj0O13XeeSRR3j00Uf3cMt2D8899xzT09OcPHmSH/qhH+LixYt7vUm7jnPnzjE7O9vxOWezWR544IED+zkDfPazn2V8fJybb76Z97znPf9/e3f00tQfhgH8EedZRNGSybaKjalliBq4aIzIm0UkXUTdGHUhFEmlUFCRBV3UTV0F1R+QN8GISISuKnW7CIu0jSnRYGNkwUwSWta0wj2/i3Awm0q69f2d0/uBA4edAz4vD4MXd8YwNTWlOtKqpdNpAEBlZSUAYGRkBD9//szrdvv27XA6nYboduG88+7fvw+r1YqGhgZcvnwZmUxGRbyimZubQyAQwLdv3+Dz+Qzf68J55xmp187OThw4cCCvQ6A079n/9Y/eLefTp0+Ym5uDzWbLe91ms+Ht27eKUpWO1+tFT08P6urqkEqlcO3aNezZswdjY2NYv3696nglMzExAQAFe56/ZjT79+/H4cOH4Xa7kUgkcOXKFbS2tmJoaAjl5eWq461INpvFuXPnsHv3bjQ0NAD41a2mabBYLHn3GqHbQvMCwNGjR+FyubBp0yZEo1FcunQJsVgMjx49Uph2ZUZHR+Hz+TA7O4t169aht7cX9fX1iEQihux1sXkBY/UaCATw+vVrvHr16rdrpXjP6noR+de0trbmzpuamuD1euFyufDgwQOcOHFCYTJRbEeOHMmdNzY2oqmpCTU1NQgGg/D7/QqTrVxnZyfGxsYM81zTchabt6OjI3fe2NgIh8MBv9+PRCKBmpqavx1zVerq6hCJRJBOp/Hw4UO0t7cjFAqpjlUyi81bX19vmF7fv3+Ps2fP4unTp1izZs1f+Zu6/mjGarWivLz8t6d1P378CLvdrijV32OxWLBt2zbE43HVUUpqvst/tWcAqK6uhtVq1W3XXV1dePz4MQYHB7Fly5bc63a7HT9+/MDnz5/z7td7t4vNW4jX6wUAXXaraRpqa2vh8Xhw48YN7NixA7dv3zZsr4vNW4heex0ZGcHk5CSam5thMplgMpkQCoVw584dmEwm2Gy2oner60VE0zR4PB709/fnXstms+jv78/73M6ovn79ikQiAYfDoTpKSbndbtjt9ryev3z5gpcvX/4TPQPAhw8fMDU1pbuuSaKrqwu9vb0YGBiA2+3Ou+7xeFBRUZHXbSwWw/j4uC67XW7eQiKRCADorttCstksvn//brheFzM/byF67dXv92N0dBSRSCR37Ny5E8eOHcudF73b1T9bq1YgEKDZbGZPTw/fvHnDjo4OWiwWTkxMqI5WdOfPn2cwGGQymeTz58+5d+9eWq1WTk5Oqo62atPT0wyHwwyHwwTAW7duMRwO8927dyTJmzdv0mKxsK+vj9FolAcPHqTb7ebMzIzi5Cuz1LzT09O8cOECh4aGmEwm+ezZMzY3N3Pr1q2cnZ1VHf2PnD59mhs2bGAwGGQqlcodmUwmd8+pU6fodDo5MDDA4eFh+nw++nw+halXbrl54/E4r1+/zuHhYSaTSfb19bG6upotLS2Kk/+57u5uhkIhJpNJRqNRdnd3s6ysjE+ePCFprF7Jpec1Uq+FLPxGULG71f0iQpJ3796l0+mkpmnctWsXX7x4oTpSSbS1tdHhcFDTNG7evJltbW2Mx+OqYxXF4OAgAfx2tLe3k/z1Fd6rV6/SZrPRbDbT7/czFoupDb0KS82byWS4b98+VlVVsaKigi6XiydPntTlcl1oRgC8d+9e7p6ZmRmeOXOGGzdu5Nq1a3no0CGmUil1oVdhuXnHx8fZ0tLCyspKms1m1tbW8uLFi0yn02qDr8Dx48fpcrmoaRqrqqro9/tzSwhprF7Jpec1Uq+FLFxEit1tGUmu7H8pQgghhBCro+tnRIQQQgihb7KICCGEEEIZWUSEEEIIoYwsIkIIIYRQRhYRIYQQQigji4gQQgghlJFFRAghhBDKyCIihBBCCGVkERFCCCGEMrKICCGEEEIZWUSEEEIIoYwsIkIIIYRQ5j8kP/pTWzk1zgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "show_mfcc(no_waveform, no_sample_rate)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 基于频谱图创建图像"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_spectrogram_images(trainloader, label_dir):\n",
    "    # make directory\n",
    "    directory = f'./data/spectrograms/{label_dir}/'\n",
    "    if os.path.isdir(directory):\n",
    "        print(\"Data exists for\", label_dir)\n",
    "    else:\n",
    "        os.makedirs(directory, mode=0o777, exist_ok=True)\n",
    "\n",
    "        for i, data in enumerate(trainloader):\n",
    "            waveform = data[0]\n",
    "            sample_rate = data[1][0]\n",
    "            label = data[2]\n",
    "            ID = data[3]\n",
    "\n",
    "            # create transformed waveforms\n",
    "            spectrogram_tensor = torchaudio.transforms.Spectrogram()(waveform)\n",
    "\n",
    "            fig = plt.figure()\n",
    "            plt.imsave(\n",
    "                f'./data/spectrograms/{label_dir}/spec_img{i}.png',\n",
    "                spectrogram_tensor[0].log2()[0, :, :].numpy(),\n",
    "                cmap='viridis',\n",
    "            )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_mfcc_images(trainloader, label_dir):\n",
    "    # make directory\n",
    "    os.makedirs(f'./data/mfcc_spectrograms/{label_dir}/', mode=0o777, exist_ok=True)\n",
    "\n",
    "    for i, data in enumerate(trainloader):\n",
    "        waveform = data[0]\n",
    "        sample_rate = data[1][0]\n",
    "        label = data[2]\n",
    "        ID = data[3]\n",
    "\n",
    "        mfcc_spectrogram = torchaudio.transforms.MFCC(sample_rate=sample_rate)(waveform)\n",
    "\n",
    "        plt.figure()\n",
    "        fig1 = plt.gcf()\n",
    "        plt.imshow(mfcc_spectrogram[0].log2()[0, :, :].numpy(), cmap='viridis')\n",
    "        plt.draw()\n",
    "        fig1.savefig(f'./data/mfcc_spectrograms/{label_dir}/spec_img{i}.png', dpi=100)\n",
    "\n",
    "        # spectorgram_train.append([spectrogram_tensor, label, sample_rate, ID])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data exists for yes\n",
      "Data exists for no\n"
     ]
    }
   ],
   "source": [
    "create_spectrogram_images(trainloader_yes, 'yes')\n",
    "create_spectrogram_images(trainloader_no, 'no')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "from torch.utils.data import DataLoader\n",
    "from torchvision import datasets, transforms\n",
    "import torch\n",
    "import torchaudio\n",
    "import torch.nn as nn\n",
    "import torch.nn.functional as F\n",
    "import torch.optim as optim\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from torch.utils.data import Dataset, DataLoader\n",
    "from torchvision import datasets, models, transforms\n",
    "import pandas as pd\n",
    "import os"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 加载频谱图到 DataLoader 进行训练"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dataset ImageFolder\n",
      "    Number of datapoints: 7985\n",
      "    Root location: ./data/spectrograms\n",
      "    StandardTransform\n",
      "Transform: Compose(\n",
      "               Resize(size=(201, 81), interpolation=bilinear, max_size=None, antialias=warn)\n",
      "               ToTensor()\n",
      "           )\n"
     ]
    }
   ],
   "source": [
    "data_path = './data/spectrograms'  # looking in subfolder train\n",
    "\n",
    "yes_no_dataset = datasets.ImageFolder(\n",
    "    root=data_path,\n",
    "    transform=transforms.Compose([transforms.Resize((201, 81)), transforms.ToTensor()]),\n",
    ")\n",
    "print(yes_no_dataset)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Class category and index of the images: {'no': 0, 'yes': 1}\n",
      "\n"
     ]
    }
   ],
   "source": [
    "class_map = yes_no_dataset.class_to_idx\n",
    "\n",
    "print(\"\\nClass category and index of the images: {}\\n\".format(class_map))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 划分训练数据和测试数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training size: 6388\n",
      "Testing size: 1597\n"
     ]
    }
   ],
   "source": [
    "# split data to test and train\n",
    "# use 80% to train\n",
    "train_size = int(0.8 * len(yes_no_dataset))\n",
    "test_size = len(yes_no_dataset) - train_size\n",
    "yes_no_train_dataset, yes_no_test_dataset = torch.utils.data.random_split(\n",
    "    yes_no_dataset, [train_size, test_size]\n",
    ")\n",
    "\n",
    "print(\"Training size:\", len(yes_no_train_dataset))\n",
    "print(\"Testing size:\", len(yes_no_test_dataset))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Counter({0: 3193, 1: 3195})"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from collections import Counter\n",
    "\n",
    "# labels in training set\n",
    "train_classes = [label for _, label in yes_no_train_dataset]\n",
    "Counter(train_classes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_dataloader = torch.utils.data.DataLoader(\n",
    "    yes_no_train_dataset, batch_size=15, num_workers=2, shuffle=True\n",
    ")\n",
    "\n",
    "test_dataloader = torch.utils.data.DataLoader(\n",
    "    yes_no_test_dataset, batch_size=15, num_workers=2, shuffle=True\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([0.4745, 0.5451, 0.5333, 0.4275, 0.4745, 0.2235, 0.5255, 0.2510, 0.4471,\n",
      "        0.1725, 0.1176, 0.5529, 0.3098, 0.5255, 0.4667, 0.1294, 0.3412, 0.3255,\n",
      "        0.5451, 0.3490, 0.4863, 0.5137, 0.4667, 0.6235, 0.2196, 0.1725, 0.4039,\n",
      "        0.5451, 0.3333, 0.2078, 0.4941, 0.3020, 0.3490, 0.3569, 0.4667, 0.4863,\n",
      "        0.5451, 0.4118, 0.5059, 0.4863, 0.6039, 0.5922, 0.6039, 0.5137, 0.3922,\n",
      "        0.5725, 0.5725, 0.4667, 0.1176, 0.5333, 0.5725, 0.4392, 0.3922, 0.5255,\n",
      "        0.5059, 0.4196, 0.4549, 0.3098, 0.4196, 0.4549, 0.1333, 0.4196, 0.4392,\n",
      "        0.4549, 0.4863, 0.6863, 0.6353, 0.3922, 0.6549, 0.4941, 0.6235, 0.4471,\n",
      "        0.3255, 0.2235, 0.4863, 0.5451, 0.4667, 0.5137, 0.2667, 0.6235, 0.5725])\n"
     ]
    }
   ],
   "source": [
    "td = train_dataloader.dataset[0][0][0][0]\n",
    "print(td)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using cuda device\n"
     ]
    }
   ],
   "source": [
    "device = 'cuda' if torch.cuda.is_available() else 'cpu'\n",
    "print('Using {} device'.format(device))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 构建卷积神经网络"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "class CNNet(nn.Module):\n",
    "    def __init__(self):\n",
    "        super().__init__()\n",
    "        self.conv1 = nn.Conv2d(3, 32, kernel_size=5)\n",
    "        self.conv2 = nn.Conv2d(32, 64, kernel_size=5)\n",
    "        self.conv2_drop = nn.Dropout2d()\n",
    "        self.flatten = nn.Flatten()\n",
    "        self.fc1 = nn.Linear(51136, 50)\n",
    "        self.fc2 = nn.Linear(50, 2)\n",
    "\n",
    "    def forward(self, x):\n",
    "        x = F.relu(F.max_pool2d(self.conv1(x), 2))\n",
    "        x = F.relu(F.max_pool2d(self.conv2_drop(self.conv2(x)), 2))\n",
    "        # x = x.view(x.size(0), -1)\n",
    "        x = self.flatten(x)\n",
    "        x = F.relu(self.fc1(x))\n",
    "        x = F.dropout(x, training=self.training)\n",
    "        x = F.relu(self.fc2(x))\n",
    "        return F.log_softmax(x, dim=1)\n",
    "\n",
    "\n",
    "model = CNNet().to(device)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 构建训练和测试函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "# cost function used to determine best parameters\n",
    "cost = torch.nn.CrossEntropyLoss()\n",
    "\n",
    "# used to create optimal parameters\n",
    "learning_rate = 0.0001\n",
    "optimizer = torch.optim.Adam(model.parameters(), lr=learning_rate)\n",
    "\n",
    "# Create the training function\n",
    "\n",
    "\n",
    "def train(dataloader, model, loss, optimizer):\n",
    "    model.train()\n",
    "    size = len(dataloader.dataset)\n",
    "    for batch, (X, Y) in enumerate(dataloader):\n",
    "        X, Y = X.to(device), Y.to(device)\n",
    "        optimizer.zero_grad()\n",
    "        pred = model(X)\n",
    "        loss = cost(pred, Y)\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "\n",
    "        if batch % 100 == 0:\n",
    "            loss, current = loss.item(), batch * len(X)\n",
    "            print(f'loss: {loss:>7f}  [{current:>5d}/{size:>5d}]')\n",
    "\n",
    "\n",
    "# Create the validation/test function\n",
    "\n",
    "\n",
    "def test(dataloader, model):\n",
    "    size = len(dataloader.dataset)\n",
    "    model.eval()\n",
    "    test_loss, correct = 0, 0\n",
    "\n",
    "    with torch.no_grad():\n",
    "        for batch, (X, Y) in enumerate(dataloader):\n",
    "            X, Y = X.to(device), Y.to(device)\n",
    "            pred = model(X)\n",
    "\n",
    "            test_loss += cost(pred, Y).item()\n",
    "            correct += (pred.argmax(1) == Y).type(torch.float).sum().item()\n",
    "\n",
    "    test_loss /= size\n",
    "    correct /= size\n",
    "\n",
    "    print(f'\\nTest Error:\\nacc: {(100*correct):>0.1f}%, avg loss: {test_loss:>8f}\\n')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 训练模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1\n",
      "-------------------------------\n",
      "loss: 0.693147  [    0/ 6388]\n",
      "loss: 0.678901  [ 1500/ 6388]\n",
      "loss: 0.443748  [ 3000/ 6388]\n",
      "loss: 0.523017  [ 4500/ 6388]\n",
      "loss: 0.512554  [ 6000/ 6388]\n",
      "\n",
      "Test Error:\n",
      "acc: 91.4%, avg loss: 0.014311\n",
      "\n",
      "Epoch 2\n",
      "-------------------------------\n",
      "loss: 0.232422  [    0/ 6388]\n",
      "loss: 0.589198  [ 1500/ 6388]\n",
      "loss: 0.150064  [ 3000/ 6388]\n",
      "loss: 0.189455  [ 4500/ 6388]\n",
      "loss: 0.152220  [ 6000/ 6388]\n",
      "\n",
      "Test Error:\n",
      "acc: 92.7%, avg loss: 0.012255\n",
      "\n",
      "Epoch 3\n",
      "-------------------------------\n",
      "loss: 0.045995  [    0/ 6388]\n",
      "loss: 0.130162  [ 1500/ 6388]\n",
      "loss: 0.151662  [ 3000/ 6388]\n",
      "loss: 0.162012  [ 4500/ 6388]\n",
      "loss: 0.914063  [ 6000/ 6388]\n",
      "\n",
      "Test Error:\n",
      "acc: 93.4%, avg loss: 0.010353\n",
      "\n",
      "Epoch 4\n",
      "-------------------------------\n",
      "loss: 0.075109  [    0/ 6388]\n",
      "loss: 0.336659  [ 1500/ 6388]\n",
      "loss: 0.084331  [ 3000/ 6388]\n",
      "loss: 0.118936  [ 4500/ 6388]\n",
      "loss: 0.131541  [ 6000/ 6388]\n",
      "\n",
      "Test Error:\n",
      "acc: 94.4%, avg loss: 0.009808\n",
      "\n",
      "Epoch 5\n",
      "-------------------------------\n",
      "loss: 0.085149  [    0/ 6388]\n",
      "loss: 0.173272  [ 1500/ 6388]\n",
      "loss: 0.296961  [ 3000/ 6388]\n",
      "loss: 0.057803  [ 4500/ 6388]\n",
      "loss: 0.119692  [ 6000/ 6388]\n",
      "\n",
      "Test Error:\n",
      "acc: 94.2%, avg loss: 0.009273\n",
      "\n",
      "Epoch 6\n",
      "-------------------------------\n",
      "loss: 0.476337  [    0/ 6388]\n",
      "loss: 0.116197  [ 1500/ 6388]\n",
      "loss: 0.058058  [ 3000/ 6388]\n",
      "loss: 0.086271  [ 4500/ 6388]\n",
      "loss: 0.248736  [ 6000/ 6388]\n",
      "\n",
      "Test Error:\n",
      "acc: 94.4%, avg loss: 0.008735\n",
      "\n",
      "Epoch 7\n",
      "-------------------------------\n",
      "loss: 0.077507  [    0/ 6388]\n",
      "loss: 0.100408  [ 1500/ 6388]\n",
      "loss: 0.831771  [ 3000/ 6388]\n",
      "loss: 0.111290  [ 4500/ 6388]\n",
      "loss: 0.106297  [ 6000/ 6388]\n",
      "\n",
      "Test Error:\n",
      "acc: 94.9%, avg loss: 0.008226\n",
      "\n",
      "Epoch 8\n",
      "-------------------------------\n",
      "loss: 0.120034  [    0/ 6388]\n",
      "loss: 0.148116  [ 1500/ 6388]\n",
      "loss: 0.136060  [ 3000/ 6388]\n",
      "loss: 0.082970  [ 4500/ 6388]\n",
      "loss: 0.011689  [ 6000/ 6388]\n",
      "\n",
      "Test Error:\n",
      "acc: 95.4%, avg loss: 0.008405\n",
      "\n",
      "Epoch 9\n",
      "-------------------------------\n",
      "loss: 0.173588  [    0/ 6388]\n",
      "loss: 0.092450  [ 1500/ 6388]\n",
      "loss: 0.111218  [ 3000/ 6388]\n",
      "loss: 0.132205  [ 4500/ 6388]\n",
      "loss: 0.119570  [ 6000/ 6388]\n",
      "\n",
      "Test Error:\n",
      "acc: 95.7%, avg loss: 0.007495\n",
      "\n",
      "Epoch 10\n",
      "-------------------------------\n",
      "loss: 0.090931  [    0/ 6388]\n",
      "loss: 0.037991  [ 1500/ 6388]\n",
      "loss: 0.082023  [ 3000/ 6388]\n",
      "loss: 0.321072  [ 4500/ 6388]\n",
      "loss: 0.166948  [ 6000/ 6388]\n",
      "\n",
      "Test Error:\n",
      "acc: 95.8%, avg loss: 0.007072\n",
      "\n",
      "Epoch 11\n",
      "-------------------------------\n",
      "loss: 0.026505  [    0/ 6388]\n",
      "loss: 0.081491  [ 1500/ 6388]\n",
      "loss: 0.039262  [ 3000/ 6388]\n",
      "loss: 0.257153  [ 4500/ 6388]\n",
      "loss: 0.204995  [ 6000/ 6388]\n",
      "\n",
      "Test Error:\n",
      "acc: 95.7%, avg loss: 0.007461\n",
      "\n",
      "Epoch 12\n",
      "-------------------------------\n",
      "loss: 0.167367  [    0/ 6388]\n",
      "loss: 0.077338  [ 1500/ 6388]\n",
      "loss: 0.048410  [ 3000/ 6388]\n",
      "loss: 0.153318  [ 4500/ 6388]\n",
      "loss: 0.030383  [ 6000/ 6388]\n",
      "\n",
      "Test Error:\n",
      "acc: 95.9%, avg loss: 0.006969\n",
      "\n",
      "Epoch 13\n",
      "-------------------------------\n",
      "loss: 0.054312  [    0/ 6388]\n",
      "loss: 0.135297  [ 1500/ 6388]\n",
      "loss: 0.121914  [ 3000/ 6388]\n",
      "loss: 0.141828  [ 4500/ 6388]\n",
      "loss: 0.064397  [ 6000/ 6388]\n",
      "\n",
      "Test Error:\n",
      "acc: 95.9%, avg loss: 0.007261\n",
      "\n",
      "Epoch 14\n",
      "-------------------------------\n",
      "loss: 0.081329  [    0/ 6388]\n",
      "loss: 0.105171  [ 1500/ 6388]\n",
      "loss: 0.091839  [ 3000/ 6388]\n",
      "loss: 0.060654  [ 4500/ 6388]\n",
      "loss: 0.019211  [ 6000/ 6388]\n",
      "\n",
      "Test Error:\n",
      "acc: 96.2%, avg loss: 0.006350\n",
      "\n",
      "Epoch 15\n",
      "-------------------------------\n",
      "loss: 0.027931  [    0/ 6388]\n",
      "loss: 0.088221  [ 1500/ 6388]\n",
      "loss: 0.165891  [ 3000/ 6388]\n",
      "loss: 0.177692  [ 4500/ 6388]\n",
      "loss: 0.019100  [ 6000/ 6388]\n",
      "\n",
      "Test Error:\n",
      "acc: 95.9%, avg loss: 0.006869\n",
      "\n",
      "Done!\n"
     ]
    }
   ],
   "source": [
    "epochs = 15\n",
    "\n",
    "for t in range(epochs):\n",
    "    print(f'Epoch {t+1}\\n-------------------------------')\n",
    "    train(train_dataloader, model, cost, optimizer)\n",
    "    test(test_dataloader, model)\n",
    "print('Done!')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 测试模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted:\n",
      "value=0, class_name= no\n",
      "\n",
      "Actual:\n",
      "value=0, class_name= no\n",
      "\n"
     ]
    }
   ],
   "source": [
    "model.eval()\n",
    "test_loss, correct = 0, 0\n",
    "class_map = ['no', 'yes']\n",
    "\n",
    "with torch.no_grad():\n",
    "    for batch, (X, Y) in enumerate(test_dataloader):\n",
    "        X, Y = X.to(device), Y.to(device)\n",
    "        pred = model(X)\n",
    "        print(\n",
    "            \"Predicted:\\nvalue={}, class_name= {}\\n\".format(\n",
    "                pred[0].argmax(0), class_map[pred[0].argmax(0)]\n",
    "            )\n",
    "        )\n",
    "        print(\"Actual:\\nvalue={}, class_name= {}\\n\".format(Y[0], class_map[Y[0]]))\n",
    "        break"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 联邦学习\n",
    "### 小节引言\n",
    "通过单机模式，我们基于微软的[教程](https://learn.microsoft.com/zh-cn/training/modules/intro-audio-classification-pytorch/) 完成了基于 PyTorch 的音频分类任务。接下来，我们将看到如何将单机模式下的音频分类任务迁移到隐语的联邦学习模式之下。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 数据划分\n",
    "首先为了模拟联邦学习多方参与的场景设定，我们先人为进行一下数据集划分。为方便演示，我们对数据按参与方进行均匀划分"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 查看数据集结构\n",
    "我们可以看到数据集的路径是 **\"./data/spectrograms\"**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "./data/spectrograms\n"
     ]
    }
   ],
   "source": [
    "print(data_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['yes', 'no']"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.listdir(data_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['spec_img2947.png',\n",
       " 'spec_img988.png',\n",
       " 'spec_img2426.png',\n",
       " 'spec_img3850.png',\n",
       " 'spec_img473.png',\n",
       " 'spec_img3641.png',\n",
       " 'spec_img298.png',\n",
       " 'spec_img1094.png',\n",
       " 'spec_img344.png',\n",
       " 'spec_img476.png',\n",
       " 'spec_img1127.png',\n",
       " 'spec_img3695.png',\n",
       " 'spec_img2039.png',\n",
       " 'spec_img724.png',\n",
       " 'spec_img354.png',\n",
       " 'spec_img3701.png',\n",
       " 'spec_img1603.png',\n",
       " 'spec_img1092.png',\n",
       " 'spec_img3040.png',\n",
       " 'spec_img3133.png']"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "subdataset_yes_path = os.path.join(data_path, 'yes')\n",
    "os.listdir(subdataset_yes_path)[:20]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 给定参与方\n",
    "我们假定联邦学习的数据拥有方是 **alice** 和 **bob**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "parties_list = ['alice', 'bob']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 建立数据文件夹\n",
    "\n",
    "由上述结果，我们可以看到，语音分类的训练数据集经过预处理后，主要由频谱图组成，并且包含两个种类：是（yes）和否（no），分别位于 **\"./data/spectrograms/yes\"** 和 **\"./data/spectrograms/no\"** ；联邦学习模型的数据输入从此处开始；我们的参与方数据文件夹分别为 **\"./fl-data/spectrograms/alice/\"** 和 **\"./fl-data/spectrograms/bob/\"**；所以我们分别在参与方数据文件夹下建立 **'yes'** 和 **'no'** 来保存对应的数据。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset_name = \"spectrograms\"\n",
    "parties_path_list = []\n",
    "split_dataset_path = os.path.join('.', 'fl-data', dataset_name)\n",
    "\n",
    "for party in parties_list:\n",
    "    party_path = os.path.join('.', 'fl-data', dataset_name, party)\n",
    "    os.makedirs(party_path, exist_ok=True)\n",
    "    parties_path_list.append(party_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['./fl-data/spectrograms/alice', './fl-data/spectrograms/bob']"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "parties_path_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "commands = os.listdir(data_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "if 'README.md' in commands:\n",
    "    commands.remove('README.md')\n",
    "elif '.DS_Store' in commands:\n",
    "    commands.remove('.DS_Store')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['yes', 'no']"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "commands"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 进行数据集划分"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "./fl-data/spectrograms/alice/yes\n",
      "./fl-data/spectrograms/bob/yes\n",
      "./fl-data/spectrograms/alice/no\n",
      "./fl-data/spectrograms/bob/no\n"
     ]
    }
   ],
   "source": [
    "from os.path import join\n",
    "import shutil\n",
    "\n",
    "parties_num = len(parties_list)\n",
    "for command in commands:\n",
    "    command_path = join(data_path, command)\n",
    "    for party_path in parties_path_list:\n",
    "        party_command_path = join(party_path, command)\n",
    "        print(party_command_path)\n",
    "        os.makedirs(party_command_path, exist_ok=True)\n",
    "\n",
    "    index = 0\n",
    "    for wav_name in os.listdir(command_path):\n",
    "        wav_path = join(command_path, wav_name)\n",
    "        target_dir_path = join(\n",
    "            '.', 'fl-data', dataset_name, parties_list[index % parties_num], command\n",
    "        )\n",
    "        shutil.copy(wav_path, target_dir_path)\n",
    "        # if you want to watch the progress of copying the files, please uncomment the following line\n",
    "        # print(f'copy {wav_path}-->{target_dir_path}')\n",
    "        index += 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "查看参与方的各个文件夹下所拥有的文件数目"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "./fl-data/spectrograms/alice/yes : 2022\n",
      "./fl-data/spectrograms/bob/yes : 2022\n",
      "./fl-data/spectrograms/alice/no : 1971\n",
      "./fl-data/spectrograms/bob/no : 1970\n"
     ]
    }
   ],
   "source": [
    "for command in commands:\n",
    "    for party_path in parties_path_list:\n",
    "        command_path = join(party_path, command)\n",
    "        file_num = len(os.listdir(command_path))\n",
    "        print(f'{command_path} : {file_num}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 隐语环境初始化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The version of SecretFlow: 1.2.0.dev20231009\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-10-24 01:03:11,117\tINFO worker.py:1538 -- Started a local Ray instance.\n"
     ]
    }
   ],
   "source": [
    "import secretflow as sf\n",
    "\n",
    "# Check the version of your SecretFlow\n",
    "print('The version of SecretFlow: {}'.format(sf.__version__))\n",
    "\n",
    "# In case you have a running secretflow runtime already.\n",
    "sf.shutdown()\n",
    "sf.init(['alice', 'bob', 'charlie'], address=\"local\", log_to_driver=False)\n",
    "alice, bob, charlie = sf.PYU('alice'), sf.PYU('bob'), sf.PYU('charlie')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 封装 DataBuilder\n",
    "\n",
    "在迁移过程，对于数据集的预处理方式，联邦学习模式和单机模式是一样的，我们不再重复。为了完成迁移适配过程，我们只需要参考[在 SecretFlow 中使用自定义 DataBuilder（Torch）](https://github.com/secretflow/secretflow/blob/main/docs/tutorial/CustomDataLoaderTorch.ipynb) 封装我们自定义 DataBuilder 即可。现在，参考原教程，我们封装对应的DataBuilder。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_dataset_builder(\n",
    "    batch_size=32,\n",
    "    train_split=0.8,\n",
    "    shuffle=True,\n",
    "    random_seed=1234,\n",
    "):\n",
    "    def dataset_builder(data_path, stage=\"train\"):\n",
    "        \"\"\" \"\"\"\n",
    "        import math\n",
    "\n",
    "        import numpy as np\n",
    "        from torch.utils.data import DataLoader\n",
    "        from torch.utils.data.sampler import SubsetRandomSampler\n",
    "        from torchvision import datasets, transforms\n",
    "\n",
    "        # Define dataset\n",
    "        yes_no_dataset = datasets.ImageFolder(\n",
    "            root=data_path,\n",
    "            transform=transforms.Compose(\n",
    "                [transforms.Resize((201, 81)), transforms.ToTensor()]\n",
    "            ),\n",
    "        )\n",
    "\n",
    "        dataset_size = len(yes_no_dataset)\n",
    "        # Define sampler\n",
    "\n",
    "        indices = list(range(dataset_size))\n",
    "        if shuffle:\n",
    "            np.random.seed(random_seed)\n",
    "            np.random.shuffle(indices)\n",
    "        split = int(np.floor(train_split * dataset_size))\n",
    "        train_indices, val_indices = indices[:split], indices[split:]\n",
    "        train_sampler = SubsetRandomSampler(train_indices)\n",
    "        valid_sampler = SubsetRandomSampler(val_indices)\n",
    "\n",
    "        # Define databuilder\n",
    "        train_loader = DataLoader(\n",
    "            yes_no_dataset, batch_size=batch_size, sampler=train_sampler\n",
    "        )\n",
    "        valid_loader = DataLoader(\n",
    "            yes_no_dataset, batch_size=batch_size, sampler=valid_sampler\n",
    "        )\n",
    "\n",
    "        # Return\n",
    "        if stage == \"train\":\n",
    "            train_step_per_epoch = math.ceil(split / batch_size)\n",
    "\n",
    "            return train_loader, train_step_per_epoch\n",
    "        elif stage == \"eval\":\n",
    "            eval_step_per_epoch = math.ceil((dataset_size - split) / batch_size)\n",
    "            return valid_loader, eval_step_per_epoch\n",
    "\n",
    "    return dataset_builder"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 构建 dataset_builder_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "# prepare dataset dict\n",
    "data_builder_dict = {\n",
    "    alice: create_dataset_builder(\n",
    "        batch_size=32,\n",
    "        train_split=0.8,\n",
    "        shuffle=False,\n",
    "        random_seed=1234,\n",
    "    ),\n",
    "    bob: create_dataset_builder(\n",
    "        batch_size=32,\n",
    "        train_split=0.8,\n",
    "        shuffle=False,\n",
    "        random_seed=1234,\n",
    "    ),\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 定义网络结构\n",
    "得益于隐语优异的设计，我们只需要将单机模式下定义的网络结构，由原来的继承`torch.nn.Module`改为继承即可`secretflow.ml.nn.utils.BaseModule`即可。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-10-24 01:03:13.883499: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory\n",
      "2023-10-24 01:03:13.883589: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory\n",
      "2023-10-24 01:03:13.883597: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.\n"
     ]
    }
   ],
   "source": [
    "from secretflow.ml.nn.utils import BaseModule\n",
    "\n",
    "\n",
    "class ConvNet(BaseModule):\n",
    "    def __init__(self, *args, **kwargs) -> None:\n",
    "        super().__init__(*args, **kwargs)\n",
    "        self.conv1 = nn.Conv2d(3, 32, kernel_size=5)\n",
    "        self.conv2 = nn.Conv2d(32, 64, kernel_size=5)\n",
    "        self.conv2_drop = nn.Dropout2d()\n",
    "        self.flatten = nn.Flatten()\n",
    "        self.fc1 = nn.Linear(51136, 50)\n",
    "        self.fc2 = nn.Linear(50, 2)\n",
    "\n",
    "    def forward(self, x):\n",
    "        x = F.relu(F.max_pool2d(self.conv1(x), 2))\n",
    "        x = F.relu(F.max_pool2d(self.conv2_drop(self.conv2(x)), 2))\n",
    "        # x = x.view(x.size(0), -1)\n",
    "        x = self.flatten(x)\n",
    "        x = F.relu(self.fc1(x))\n",
    "        x = F.dropout(x, training=self.training)\n",
    "        x = F.relu(self.fc2(x))\n",
    "        return F.log_softmax(x, dim=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "from secretflow.ml.nn import FLModel\n",
    "from secretflow.security.aggregation import SecureAggregator\n",
    "from torch import nn, optim\n",
    "from torchmetrics import Accuracy, Precision\n",
    "from secretflow.ml.nn.fl.utils import metric_wrapper, optim_wrapper\n",
    "from secretflow.ml.nn.utils import TorchModel"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 定义 Torch 后端的 FLModel "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:root:Create proxy actor <class 'secretflow.security.aggregation.secure_aggregator._Masker'> with party alice.\n",
      "INFO:root:Create proxy actor <class 'secretflow.security.aggregation.secure_aggregator._Masker'> with party bob.\n",
      "INFO:root:Create proxy actor <class 'secretflow.ml.nn.fl.backend.torch.strategy.fed_avg_w.PYUFedAvgW'> with party alice.\n",
      "INFO:root:Create proxy actor <class 'secretflow.ml.nn.fl.backend.torch.strategy.fed_avg_w.PYUFedAvgW'> with party bob.\n"
     ]
    }
   ],
   "source": [
    "device_list = [alice, bob]\n",
    "aggregator = SecureAggregator(charlie, [alice, bob])\n",
    "\n",
    "\n",
    "num_classes = 2\n",
    "# torch model\n",
    "loss_fn = nn.CrossEntropyLoss\n",
    "optim_fn = optim_wrapper(optim.Adam, lr=1e-3)\n",
    "\n",
    "model_def = TorchModel(\n",
    "    model_fn=ConvNet,\n",
    "    loss_fn=loss_fn,\n",
    "    optim_fn=optim_fn,\n",
    "    metrics=[\n",
    "        metric_wrapper(\n",
    "            Accuracy, task=\"multiclass\", num_classes=num_classes, average='micro'\n",
    "        ),\n",
    "        metric_wrapper(\n",
    "            Precision, task=\"multiclass\", num_classes=num_classes, average='micro'\n",
    "        ),\n",
    "    ],\n",
    ")\n",
    "\n",
    "fed_model = FLModel(\n",
    "    device_list=device_list,\n",
    "    model=model_def,\n",
    "    aggregator=aggregator,\n",
    "    backend=\"torch\",\n",
    "    strategy=\"fed_avg_w\",\n",
    "    random_seed=1234,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 给出参与方数据集路径"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['./fl-data/spectrograms/alice', './fl-data/spectrograms/bob']"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "parties_path_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = {\n",
    "    alice: parties_path_list[0],\n",
    "    bob: parties_path_list[1],\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 训练联邦学习模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:root:FL Train Params: {'x': {PYURuntime(alice): './fl-data/spectrograms/alice', PYURuntime(bob): './fl-data/spectrograms/bob'}, 'y': None, 'batch_size': 32, 'batch_sampling_rate': None, 'epochs': 15, 'verbose': 1, 'callbacks': None, 'validation_data': {PYURuntime(alice): './fl-data/spectrograms/alice', PYURuntime(bob): './fl-data/spectrograms/bob'}, 'shuffle': False, 'class_weight': None, 'sample_weight': None, 'validation_freq': 1, 'aggregate_freq': 2, 'label_decoder': None, 'max_batch_size': 20000, 'prefetch_buffer_size': None, 'sampler_method': 'batch', 'random_seed': 1234, 'dp_spent_step_freq': 1, 'audit_log_dir': None, 'dataset_builder': {PYURuntime(alice): <function create_dataset_builder.<locals>.dataset_builder at 0x7f608933ac10>, PYURuntime(bob): <function create_dataset_builder.<locals>.dataset_builder at 0x7f6088428f70>}, 'wait_steps': 100, 'self': <secretflow.ml.nn.fl.fl_model.FLModel object at 0x7f5f2cedbd00>}\n",
      "100%|██████████| 100/100 [02:02<00:00,  1.23s/it]WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "100%|██████████| 100/100 [02:20<00:00,  1.40s/it, epoch: 1/15 -  multiclassaccuracy:0.8439023494720459  multiclassprecision:0.8439023494720459  val_multiclassaccuracy:0.8466833829879761  val_multiclassprecision:0.8466833829879761 ]\n",
      "100%|██████████| 100/100 [02:00<00:00,  1.31s/it]WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "100%|██████████| 100/100 [02:16<00:00,  1.36s/it, epoch: 2/15 -  multiclassaccuracy:0.9106001853942871  multiclassprecision:0.9106001853942871  val_multiclassaccuracy:0.7947434186935425  val_multiclassprecision:0.7947434186935425 ]\n",
      "100%|██████████| 100/100 [02:03<00:00,  1.27s/it]WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "100%|██████████| 100/100 [02:19<00:00,  1.40s/it, epoch: 3/15 -  multiclassaccuracy:0.9275089502334595  multiclassprecision:0.9275089502334595  val_multiclassaccuracy:0.8879849910736084  val_multiclassprecision:0.8879849910736084 ]\n",
      "100%|██████████| 100/100 [02:02<00:00,  1.27s/it]WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "100%|██████████| 100/100 [02:17<00:00,  1.38s/it, epoch: 4/15 -  multiclassaccuracy:0.9303278923034668  multiclassprecision:0.9303278923034668  val_multiclassaccuracy:0.8760951161384583  val_multiclassprecision:0.8760951161384583 ]\n",
      "100%|██████████| 100/100 [02:01<00:00,  1.23s/it]WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "100%|██████████| 100/100 [02:17<00:00,  1.38s/it, epoch: 5/15 -  multiclassaccuracy:0.932676374912262  multiclassprecision:0.932676374912262  val_multiclassaccuracy:0.8929912447929382  val_multiclassprecision:0.8929912447929382 ]\n",
      "100%|██████████| 100/100 [02:00<00:00,  1.24s/it]WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "100%|██████████| 100/100 [02:16<00:00,  1.36s/it, epoch: 6/15 -  multiclassaccuracy:0.9356507062911987  multiclassprecision:0.9356507062911987  val_multiclassaccuracy:0.9136420488357544  val_multiclassprecision:0.9136420488357544 ]\n",
      "100%|██████████| 100/100 [02:01<00:00,  1.24s/it]WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "100%|██████████| 100/100 [02:16<00:00,  1.37s/it, epoch: 7/15 -  multiclassaccuracy:0.9423828125  multiclassprecision:0.9423828125  val_multiclassaccuracy:0.8936170339584351  val_multiclassprecision:0.8936170339584351 ]\n",
      "100%|██████████| 100/100 [02:02<00:00,  1.27s/it]WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "100%|██████████| 100/100 [02:18<00:00,  1.38s/it, epoch: 8/15 -  multiclassaccuracy:0.9442623853683472  multiclassprecision:0.9442623853683472  val_multiclassaccuracy:0.9161452054977417  val_multiclassprecision:0.9161452054977417 ]\n",
      "100%|██████████| 100/100 [02:04<00:00,  1.26s/it]WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "100%|██████████| 100/100 [02:19<00:00,  1.40s/it, epoch: 9/15 -  multiclassaccuracy:0.9500551223754883  multiclassprecision:0.9500551223754883  val_multiclassaccuracy:0.9198998808860779  val_multiclassprecision:0.9198998808860779 ]\n",
      "100%|██████████| 100/100 [02:02<00:00,  1.26s/it]WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "100%|██████████| 100/100 [02:18<00:00,  1.39s/it, epoch: 10/15 -  multiclassaccuracy:0.950681209564209  multiclassprecision:0.950681209564209  val_multiclassaccuracy:0.9030037522315979  val_multiclassprecision:0.9030037522315979 ]\n",
      "100%|██████████| 100/100 [02:03<00:00,  1.26s/it]WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "100%|██████████| 100/100 [02:19<00:00,  1.39s/it, epoch: 11/15 -  multiclassaccuracy:0.9524033069610596  multiclassprecision:0.9524033069610596  val_multiclassaccuracy:0.9036295413970947  val_multiclassprecision:0.9036295413970947 ]\n",
      "100%|██████████| 100/100 [02:03<00:00,  1.26s/it]WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "100%|██████████| 100/100 [02:18<00:00,  1.39s/it, epoch: 12/15 -  multiclassaccuracy:0.9549084901809692  multiclassprecision:0.9549084901809692  val_multiclassaccuracy:0.9211513996124268  val_multiclassprecision:0.9211513996124268 ]\n",
      "100%|██████████| 100/100 [02:04<00:00,  1.28s/it]WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "100%|██████████| 100/100 [02:20<00:00,  1.41s/it, epoch: 13/15 -  multiclassaccuracy:0.9533429741859436  multiclassprecision:0.9533429741859436  val_multiclassaccuracy:0.9242803454399109  val_multiclassprecision:0.9242803454399109 ]\n",
      "100%|██████████| 100/100 [02:04<00:00,  1.27s/it]WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "100%|██████████| 100/100 [02:20<00:00,  1.40s/it, epoch: 14/15 -  multiclassaccuracy:0.9614846706390381  multiclassprecision:0.9614846706390381  val_multiclassaccuracy:0.9242803454399109  val_multiclassprecision:0.9242803454399109 ]\n",
      "100%|██████████| 100/100 [02:04<00:00,  1.28s/it]WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "WARNING:root:Please pay attention to local metrics, global only do naive aggregation \n",
      "100%|██████████| 100/100 [02:20<00:00,  1.40s/it, epoch: 15/15 -  multiclassaccuracy:0.9638330936431885  multiclassprecision:0.9638330936431885  val_multiclassaccuracy:0.9299123883247375  val_multiclassprecision:0.9299123883247375 ]\n"
     ]
    }
   ],
   "source": [
    "history = fed_model.fit(\n",
    "    data,\n",
    "    None,\n",
    "    validation_data=data,\n",
    "    epochs=15,\n",
    "    batch_size=32,\n",
    "    aggregate_freq=2,\n",
    "    sampler_method=\"batch\",\n",
    "    random_seed=1234,\n",
    "    dp_spent_step_freq=1,\n",
    "    dataset_builder=data_builder_dict,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 可视化训练历史"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['multiclassaccuracy', 'multiclassprecision', 'val_multiclassaccuracy', 'val_multiclassprecision'])"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "history.global_history.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "\n",
    "# Draw accuracy values for training & validation\n",
    "plt.plot(history.global_history['multiclassaccuracy'])\n",
    "plt.plot(history.global_history['val_multiclassaccuracy'])\n",
    "plt.title('FLModel accuracy')\n",
    "plt.ylabel('Accuracy')\n",
    "plt.xlabel('Epoch')\n",
    "plt.legend(['Train', 'Valid'], loc='upper left')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 小结\n",
    "可以看到，将单机模式下的音频分类任务，迁移到隐语的联邦学习模式，不仅非常的容易，而且不需要开发者继续编写训练函数和测试函数，充分展现了隐语的易用性和好用性"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 总结"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "通过本教程，您将学习到：\n",
    "- 如何基于 PyTorch 开展音频分类任务\n",
    "- 如何编写少量代码即可将单机模式下的音频分类模型迁移到隐语的联邦学习框架之下 "
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "limingbo_oscp",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.17"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
